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SP SS
Ve r si o n 1 0
/
2003
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% 1 / ; $ 2 2 % . $ 1 2 % ( g e n d e r ) K 1 – 1 . N u me ri c v a ri a b l e
. d a t e T 1 / 1 . / > ( b d a t e ) ' T 1 – ; 1 . % 1 / ( G ra d e
? " 1 " 2 - C 2 E Da t a V i e w V a ri a b l e
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) ! 1 – < 1
% # " 2 % $ 0 2 E - $ %
% 9 * $ E 8 . N a me a n d A t t ri b u t e s
N 1 # 6 $ $ (3B1) $ , # % 3 ; Da t a V i e w
13
% $ -V ie w
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(31) ? '
V a ria b le V ie w V a ria b le s N a m e s &
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: ( $ , V a ri a b l e N a me &
A t t ri b u t e s 1 " 2 - -
R " 1 ( , L .4 R 1 D
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.8 R @ E 2 E .7 R 2 E .6R 1 .5
: ( V a ri a b l e V i e w
% # ? " 1 ( 2 ;
Variable Name :
6 # I d 2 ! ' 1 2 - L - 2 N a me $ 4 . # ( 4 - E -
# E > L 7 ( " 1 E . / 6 # G e n d e r 2 ! $ ? B: SP SS # " 1 ) -
.ch a ra ct e rs & 2 ! $ 6 & !
B1
& pe ri o d @ # - % - - # - E # & E - C 1 2 - - L B2 .$ RBR# R@
.*R‘ R?
n e w v a r N EW V A R
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R ! $ & D
" = # 1 2 - I !
) ? # @ 1 C @ C SP SS & !
. " 1 ) ? @ 1 C Y $ E ! - ; (
14
B3
B4
B5
T ype $ 4 . I
Variable Type :
.: ( Di a l o g b o x H
< E @ ( 9 * $ E 1 2 $ * 3 7 ( E b u t t o n
V a r i a b l e Ty p e . E 4
'
. Da t a V i e w
& 3 ( C %
B: " 1 > ? ;
% # " 1 ( I # ! > / 4 1 : N u me ri c
L ' $ $ ( ( , ) ( # # I * < 4 1 / : C o mma
. > . / L 722, 667. 123 L 722667. 123
$ ( ( , ) ( 2
L ' $ $ ( . ) 2 < 4 1 / : Do t
L 10 ' E-n o t a t i o n
1 L & / : Sci e n t i fi c N o t a t i o n
.> . / L 722. 667, 123 L 5 ' - # 4 , ) &
7
F ) &
.1.2E+03 L 1234 1.0E+07
. ' " " % - T $ 1 : Da t e 7 6 I
. ? ! ( & $ : Do l l a r
( 9 ( ! ( C 1 : C u st o m C u rre n cy . Ed i t
O pt i o n s
C u rre n cy
.( ' ) - ) 4 & 1 / : St ri n g
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De ci ma l < 5 . / # 4 & 1 7 st ri n g > # i d 1 ( > # G ra d e g e n d e r 1 -. V a ri a b l e R a n k H
H
15
P l a ce s
3 ; Da t e > # b d a t e ' T 1 -. $ N u me ri c :
L ( 6 > d d .mm .yy % T > - - ;
.T (
N u me ri c > ) " 1 # . N u me ri c / 1 > I # ! > -
- (4 1 7 J ) 1 > Da t a V i e w 16
, , # @ , 2 % ? $ * ( 6 E #
.$ $ % 1 > L ( n u me ri c ) 4 = 1 #
1 ) , L $ * # Do t C o mma N u me ri c " 1 (
, L " . 2 E , L ( D ( # D
Da t a V i e w
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2 E (
." # 2 ( E ( 9 ( ?
9 ( - 1 E # ( & " 1 ) st ri n g .“N O ” 9 * " " N o
, ( ( & & 4 , ) &
C $ '
" & N o ( # w i d t h = 6 4 & 1 (
# ; / v a ri a b l e t ype H
Variable w id t h
# 7 / )W i d t h 1 D
D
.3
:
-
( & $ # (V a ri a b l e V i e w
= " 1 ( - " 1 # F ( G (
.1
%
& 9 E
N' . 4 = 1 ( L 1 D
$ #
E # (2 - 1) & G e n d e r 1 2 % - .10 / C o mma > 333, 333.02
- ( - - 2 % 4 - ) 1 4 W i d t h # 1 D
9
\ ! " ? 3 4 W i d t h
4 . T > & 8 / 7 I # ! W i d t h
# . 8 / W i d t h I # ! E " E # i d % # 2 ! ) &
E # g ra d e " 1
J # T 1 100
2 ! 1 -. d d .mm.yy$ . / # 5 -
) 3 ' W i d t h = 4 N' i d 2 ! 1 & $ ( % . 4 & (C ) & 9 ( 4 . * Da t a V i e w
D ec im als :
R N u me ri c) " 1 # 4 , ( , L $ N ( $ ? 9 9 ( ? 9 2 ? 6 , L G . I - V a ri a b l e T ype
H
E * @ & ( Do t R C o mma
/ , L -
Variable L abel :
9 6 ' # 1 C $ & 256 9 * 5 & $ N 1 9 6 -
16
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C ( # I C " 1 ) - E 5 . / 4 : U np aired V ariab l es ∗ & W o rk i n g Da t a F i l e
+ & Ext e rn a l Da t a F i l e
. me rg e d F i l e (
$ C ( " 1 ( &
C ( " 1 ( &
: " 1 U n pa i re d V a ri a b l e s E $ ,
. 2 ! H 6 ! ( " 1
•
; ? C ( # & " 1 ( - # " 1 2 " 1
•
. ( ' # U n e q u a l W i d t h = $ 6 - & " 1
•
. & " 1 " 1 !
% G ro u p2 C ( # pa i n t G ro u p1 C ( # mu si c
1 - 3 ' $ . / #
. ( # - H 6 2 L E 5 . / # I
& E 2 ( ? K & 5 E ) 1 , J E 5 . / % 1 4 - 2 - 1 :1 3 ' # So u rce 01 2 J
.
. 1 .
2 - ) 6 * R e n a me
1 # I * 2 . / , J : I ndic ate C ase sourc e v ariab l e
C ( " ! 1 E $ C ( " ! 0 E . J C (
# C ( 3 ( 2 A d d C a se s F ro m H
# o k
& E
: (Sa v e A s ? ) L = 2 ! 7 6 * ; ( Da t a e d i t o r , ,
M e rg e d F i l e n a me ma t h ch e m Sa mi r 100 9 0 L u b n a 9 5 8 7 Y o u si f 8 5 9 0 A mma r 9 5 8 3 Si n a n 9 0 9 2 V a ri a b l e s i n N e w % 9 * U n pa i re
ph ysc 9 5 9 0 7 7 8 2 8 6 d % # " 1 M & 4 - $ E :2 3 '
C ( ? ∗ $ C ( 1 - - 6 , 9 ( W o rk i n g Da t a F i l e
A d d ` H
# U n pa i re d % # 3 . ( pa i n t mu si c ( $ E ( # +
: " 6 < C a se s fro m
. ( 1 2 - 9 ( E < C T R L \ 6 1 I - 2 $ ? 1 E -) 1 ' .1
A d d C a se s H
36
3 ; mu si c &
pa i n t /
2 ( 1 $ E P a i r & E - .2 : (
fro m
n a me Sa mi r L u b n a Y o u si f A mma r Si n a n
ma t h 100 9 5 8 5 9 5 9 0
V a ri a b l e s i n N e w #
: ( ( 2 5 ' - H = O K & E M e rg e d F i l e ch e m ph ysc mu si c 9 0 9 5 8 7 8 7 9 0 8 5 9 0 7 7 8 8 8 3 8 2 9 0 9 2 8 6 9 5 . ( 1 ( mu si c 2 - ) 6 * 2 7 - 3 '
.3
% # / ' - pa i n t mu si c 1 4 - I : 3 3 '
& E 2 ( ? K & 5 E ) L ( 6 1 W o rk i n g Da t a F i l e
9 ( $ ( 1 ' I = . -) O K
& E / A d d
C a se s F ro m H
1 4 ! 4 . C ( # I " ! ( @ E % 4 4 . C (
n a me Sa mi r L u b n a Y o u si f A mma r Si n a n
ma t h 100 9 5 8 5 9 5 9 0
" ! K . (
M e rg e d F i l e ch e m ph ysc 9 0 9 5 8 7 9 0 9 0 7 7 8 3 8 2 9 2 8 6
: (
. . .
mu si c 8 7 8 5
pa i n t . . 8 8 9 0 9 5 A d d V a ri a b l e s " 1 # I - .L
C ( < ( ) $ C ( * ? . / F
. ( " 1 1 2
# 6 K " 4 Su b 2 C ( < I - # 6 " I G ro u p1 C (
: ( - I
37
n a me Sa mi r L u b n a
ma t h 100 9 5
G ro u p1 ch e m 9 0 8 7
ph ysc 9 5 9 0
mu si c 8 7 8 5
su b 2 n a me a ra b i c e n g l i sh Sa mi r 8 0 9 8 L u b n a 8 5 9 5 : " 6 < ($ ? C ( " 1 9 C ( " 1 # I * ) ( 3 # Da t a
. ($ C ( ) o pe n ? N E & G ro u p1 C ( F # -
M e rg e F i l e s
A d d
- 2 E 6 ,
V a ri a b l e s
C ( ) N E & Su b 2 C ( 7 A d d V a ri a b l e s : R e a d F i l e H
A d d
H
3 A d d V a ri a b l e s : R e a d F i l e H
. (
# o pe n & E
: ( V a ri a b l e s F ro m
: ( H I
C ( # I C " 1 ) J % / : N ew W
ork ing data F il e
. ( ' # 2 ! 7 , ! " 1 # I 2
@ C ( " 1 ) J % / : Ex c l uded V ariab l es
G ro u p1 $ C ( " 1 ) - 7 , su b 2
C ( " 1 ) - I
. ( ' # 5 N 3 (+ 5 & ) Su b 2 C ( n a me 1 I E 3 '
6 ( > ? 2 3 . #
% E C $ . 2 3 L - F % : Key Variables
# L 7 - N ( . @ E " ! - , = " ! D
9 ( ( ) N'
. K e y V a ri a b l e s # 6 ,
. 2 ! K ( ' # K e y V a ri a b l e I - L
38
.1
.K e y V a ri a b l e
L So rt i n g A sce n d i n g N ( L L
.K e y V a ri a b l e \ 1 9 * M ! $ .
( C ( 3 A d d V a ri a b l e s F ro m H
# O K & E
: (
M e rg e d F i l e n a me Sa mi r L u b n a
ma t h 100 9 5
ch e m 9 0 8 7
ph ysc 9 5 9 0
mu si c 8 7 8 5
a ra b i c 8 0 8 5
.2
e n g l i sh 9 8 9 5
(K ey v ariab l e * 5 6 ) : 2 2
C ( < (5 ' -1 $ ) 6 " 4 4 . G ro u p1 C ( - D n a me Y o u si f A mma r Si n a n Sa mi r L u b n a n a me Sa mi r L u b n a . . . "
Su b 3 a ra b i c 9 0 8 7 8 5 8 0 8 5 ma t h 100 9 5 . . . . . .
#
: ( L' 6 " 4 4 . Su b 3
e n g l i sh 8 5 9 2 9 1 9 8 9 5
: ( 3 K e y V a ri a b l e $ 2 # ch e m ph ysc mu si c a ra b i c e n g l i sh 9 0 9 5 8 7 9 0 8 5 8 7 9 0 8 5 8 7 9 2 . 8 5 9 1 . 8 0 9 8 . 8 5 9 5
9 * Su b 3 C ( # ( 6 " C I 2 ;
= ( - 3 '
: " 6 L K e y V a ri a b l e $ L 7 ( R G ro u p1 C ( # ( 6 K
? 6 n a me 1 L So rt A sce n d i n g N su b 3 G ro u p1 ( L SSu b 3 SG ru o p1 2 ( & < Da t a
39
So rt C a se s
: (
SG ro u p1 n a me ma t h ch e m ph ysc mu si c L u b n a 9 5 8 7 9 0 8 5 Sa mi r 100 9 0 9 5 8 7 SSu b 3 n a me a ra b i c e n g l i sh A mma r 8 7 9 2 L u b n a 8 5 9 5 Sa mi r 8 0 9 8 Si n a n 8 5 9 1 Y o u si f 9 0 8 5 1 / (L 1 ) n a me 1 ? ? C L % ( - 3 ! H
3 # Da t a
M e rg e F i l e s
. SG ro u p1 L C ( F # -
. 4 &
- 2 E
A d d V a ri a b l e s
: $ , 9 ( 7 2 E 4 . A d d V a ri a b l e s F ro m
B o t h F i l e s < M a t ch C a se s o n K e y V a ri a b l e i n So rt e d fi l e s , J
•
9 *
n a me A mma r L u b n a Sa mi r Si n a n Y o u si f
40
6 7 ( E - 2 @ , J n a me 1 E Excl u d e
V a ri a b l e s % #
•
: ( ( 2 5 ' - H
M e rg e d F i l e ch e m ph ysc mu si c a . . 8 7 9 0 8 5 9 0 9 5 8 7 . . . .
# o k & E
: $ , 9 ( A d d V a ri a b l e s fro m H
. . .
. P ro v i d e ca se s
ma t h
. 9 5 100 . .
3 # K e y V a ri a b l e s
ra b 8 8 8 8 9
ic
7 5 0 5 0
e n g l i sh 9 2 9 5 9 8 9 1 8 5
; C a se s " ! @ 4 C ( / : K ey ed T ab l e T ab l e L ook up f il e 7 8
# . C ( @ ! ; - C ( # " ! @ (H 6 ) $ E - $ -
# - " ( @ / N' @ " ( 6 " - " .@ ?
( 7 8 ) 3 2
$ R A g e R n a me 2 ! ) @ ? # - " ( 4 h o u se h o l d C (
: ( ( h o u sn o 2 % R Ed u
h o u se h o l d A g e 20 35 30 15 17 40 36
n a me A h ma d Z e k i Sa b a h Z a in a b I b ra h i m Sa mi r Se l ma
Ed u Se c B sc se c P ri m Se c M a B sc
h o u sn o 10 10 10 10 12 12 12
( ?
1 0
( ?
1 2
< % R Si z e @ ? 2 I ( @ ? " ( 4 # h o u se C ( Si z e 4 3 k e y V a ri a b
h o u L o ca B a g h B a g h l e /
se tio d a d a 4
: h o u sn o
2 % RL o ca t i o n
n
h o u sn o d 10 d 12 . h o u sn o 1 L N 5 ' - ( % - N (
. ( # 6 E 5 . / Da t a
so rt C a se s ?
# - # $ (h o u se C ( ) " ( % - ( 5 ' - ( -
: " 6 L 8 . . h o u se h o l d $ ? C ( # @ ?
W o rk i n g F i l e $ C ( F 4 . h o u se h o l d C ( F # -
C ( - 2 Da t a
M e rg e F i l e s
A d d V a ri a b l e s
Ext e rn a l F i l e 4 . A d d V a ri a b l e s : R e a d F i l e ` H
H
3 A d d V a ri a b l e s : R e a d F i l e ` H
Excl u d e d V a ri a b l e s % I Ext e rn a l F i l e
2 E h o u se
# o pe n & E
h o u sn o 1 9 ( 4 4 . A d d V a ri a b l e s F ro m : ( )
J 2 E ;
< M a t ch C a se s o n K e y V a ri a b l e s i n So rt e d F i l e s , J
. T a b l e L o o k U p fi l e ; C ( /
41
C ( - i s K e ye d T a b l e
•
7 ( E 2 5 , J
H
C ( h o u sn o 1 E - Excl u d e d
3 ; \ 1 5 K e y V a ri a b l e s 9 : ( @ . " )
*
n a me A h ma d Z e k i Sa b a h Z a in a b I b ra h i m Sa mi r Se l ma
A g e 20 35 30 15 17 40 36
M e rg e d F i l e Ed u h o u sn o Se c 10 B sc 10 se c 10 P ri m 10 Se c 12 M a 12 B sc 12
. $ ( D
# O K
& E
= ? " C ( ($ # ) &
L o ca t i o n B a g h d a d B a g h d a d B a g h d a d B a g h d a d B a g h d a d B a g h d a d B a g h d a d
Spl i t F i l e s (" ( &
: K L G
D
) $ #
1 ? . / $
.8
1 2
, ? L $ $
g e n d e r m f m f m f
" 6 < f ;
? L $ m . L $ $ ? -& Da t a
42
Si z e 4 4 4 4 3 3 3
6
•
A d d V a ri a b l e s F ro m
: ( ( 2 H H
w a g e 60 30 7 0 35 65 40
V a ri a b l e s % #
Spl i t F i l e
9 * C ( &
2 E 6 ,
:
: $ , 9 ( 7 % 4 . Spl i t F i l e
. C ( &
2
3
: - ;
: A nal y se A l l C ases, do not C reat G roup s
- 1 . / ) 1 " # L C ( &
E $ , 9 ( * ( D
H
2 : C omp are G roup s
2 ( G ro u ps B a se d o n # " 1 . &
1 ( <
2 C o mpa re G ro u ps E K / . / : O rg aniz e O utp ut b y G roup s
. / 2 $ . / # ) &
1 < $ ( E @ D
$ E 6 7 , . / L C ( $ # E 6 -. ( g e n d e r &
? N' " ( D (" 1 ) 1 <
1 ( %
E 6 # C ' ! C o mpa re
G ro u ps
. F re q u e n ci e s
L C ( L 2 : S ort T h e F il e b y G roup ing V ariab l e . &
@ " - 9 5 ! L L 9 M ! C ( :F il e is A l ready S orted
9 ( So rt L ( 2 & ' " % ! / . / @ # . &
1 L
. ( So rt T h e F i l e b y G ro u pi n g V a ri a b l e ) H * . / 2 ! L( = ?
m . ( / - -&
9 * C ( &
2 Spl i t F i l e H
# O K
& E
: ( g e n d e r 1 ( ? C L So rt L 2 % f ; ] ? w a g e g e n d e r 30 f 35 f 40 f 60 m 7 0 m 65 m
43
H C o mpa re g ro u ps , J # L K 9 $ - N (
? w a g e 1 ( 6 L ( # " ( " # 3
L $
< $ 3 -)A n a l yz e
De scri pt i v e St a t i st i cs
F re q u e n ci e s
: " ( F re q u e n ci e s ? 6
Frequencies G E N D E R = f
O rg a n i z e O u t pu t b y G ro u ps "
.1
: co mpa re g ro u ps "
.2
Statisticsa WAGE N V a lid M is s in g M e a n
a . GEND ER = f
3 0 35 . 00
G E N D E R = m Statisticsa WAGE N V a lid M is s in g M e a n
a . GEND ER = m
3 0 6 5 . 00
Frequencies Statistics WAGE f
N
m
M e a n N M e a n
V a lid M is s in g V a lid M is s in g
3 0 35 . 00 3 0 6 5 . 00
H 6 L 2001 2000 # $ M ? $ : 2 2 pro d 800 600 1400 900
44
ye a r 2000 2000 2001 2000
re g i o n N o rt h So u t h N o rt h N o rt h
( R , )
1090 950 1350 1180 700 975 1290 1000 750 1310 1150
2001 2000 2001 2001 2000 2000 2001 2001 2000 2001 2001
So u t h N o rt h N o rt h So u t h So u t h N o rt h N o rt h So u t h So u t h N o rt h So u t h . E 6 L (pro d M 1 ) C ( &
< $ I
H 6 L $ pro d 1 " ! - ; C ( &
2 E 4 . Spl i t F i l e
H
3 # Da t a
: $ pro d 8 00 9 00 9 50 _ _ _ _ _ _ _ _ _ 9 7 5 600 7 00 7 50 _ _ _ _ _ _ _ _ _ 1400 1350 129 0 1310 _ _ _ _ _ _ _ _ _ 109 0
< re g i o n N o rt h N o rt h N o rt h _ _ _ _ _ _ _ _ _ N o rt h So u t h So u t h So u t h _ _ _ _ _ _ _ _ _ N o rt h N o rt h N o rt h N o rt h _ _ _ _ _ _ _ _ _ So u t h
- 9 C ( &
45
, # ye a r 2000 2000 2000 _ _ _ _ _ _ _ _ 2000 2000 2000 2000 _ _ _ _ _ _ _ _ 2001 2001 2001 2001 _ _ _ _ _ _ _ _ 2001
Spl i t F i l e
_ _ _ _ _ _ _ _ _ _ _ _
1
: " 6
: $ , 9 ( 7
& E
1st G ro u p
_ _ _ _ _ _ _ _ _ _
D
- 2 E
2 5 ' - H # O K
_ _ _ _ _ _ _
L ( 6
2n d G ro u p
3rd G ro u p
4t h G ro u p
118 0 1000 1150
2001 2001 2001
So u t h So u t h So u t h
$ ( . / J # pro d 1 6 M ! fre q u e n ci e s ? $ ( )
-
: ( O rg a n i z e O u t pu t b y G ro u ps ? < 9 ( &
F r e q u e n c ie s Y E A R = 2 0 0 0 , R E IG O N
= N o rth
Statisticsa PROD N V a lid M is s in g M e a n
4 0 9 06 . 2 5
a . Y E A R = 2 000, RE I G ON = No r t h
Y E A R
= 2 0 0 0 , R E IG O N
= S o u th
Statisticsa PROD N V a lid M is s in g M e a n
3 0 6 8 3. 33
a . Y E A R = 2 000, RE I G ON = S o u t h
Y E A R
= 2 0 0 1 , R E IG O N
= N o rth
Statisticsa PROD N V a lid M is s in g M e a n
4 0 1 3 3 7 .5 0
a . Y E A R = 2 001 , RE I G ON = No r t h
Y E A R
= 2 0 0 1 , R E IG O N
= S o u th
Statisticsa PROD N V a lid M is s in g M e a n
4 0 1 1 05 . 00
a . Y E A R = 2 001 , RE I G ON = S o u t h
46
A g g reg ate Data 9
@ # ca se s " ! E ( " ( G
( ? . / $
L' 6 " ! 4 % " # . - $ $ 9 ( # .
.9
C (
- # L 6 N! ( @ / ) < $ # L= E # K
C ( # N' 4 C ! - $ # L' 6 " ! 6 D
4 ,
. K # L' 6 < " ! D
N!
? d e g re e 3 2 3 ) - 4 sa l a ry C (
2
: ( Da t a Ed i t o r , , # 3 sa l a ry
sa l a ry C ( n a me d e g re e sa l a ry A h ma d 3 40 Sa me r 3 35 L o a y 3 50 M a h mo o d 1 8 0 A ya d 1 7 0 Y a ssi n 2 66 Sa t a r 1 8 5 R a z a k 1 7 7 K a ma l 2 59 A b a s 3 45 M a h d i 1 9 0 Sa l i m 2 62 Sa b a h 2 57 F a la h 2 55 I ma d 1 8 2 .d e g re e 3 L ( 6 M ) L 1 < L ( 6 A g g re g a t e ` H
47
3 # Da t a
: " 6 < 8 . .
A g g re g a t e
- 2 E 6 ,
: ( 7 4 . Da t a
(" ! ) < C $ b re a k d o w n V a ri a b l e (s) &
: - ;
(" 1 ) 1 / :B reak
. < d e g re e 3 1 ( $ . / #
" ! < # L= 4 . (" 1 ) 1 / : A g g reg ate V ariab l e(s) . &
1 L
A g g re g a t e V a ri a b l e (s) % 9 7 ( E sa l a ry / 1 J # $ . / # : 7 N ( 3 $ 4 ,
2 E N a me &
Q 6 $ sa l a ry_ 1 / I # 2 J 3 7 J #
L a b e l & $ 7 1 ( I # ! 2 ? 1
•
1 2 E F u n ct i o n & E ( M e a n 6 ) I # ! 1
•
. A g g re g a t e V a ri a b l e s % % 1
Su m R St a n d a rd De v i a t i o n $ Y - $ - ; A g g re g a t e V a ri a b l e s % %
. T …N o . o f C a se s Ro f C a se s
2 7 < , J : S av e N umb er of c ases in b reak G roup as v ariab l e
9 ? 3 ( N' # $ " ! N _ B re a k / I # 2 J
1
. 4 ( 5 3 ( 6 E 1 . J
I # 2 J " ( 4
C ( F . / : C reat new
Data F il e
1 7 N ( . : ( sa l a ry ( ? C ( 7 # < E 4 . $ K # A g g r /
. F i l e & E 7 % C ( 2 -
8 . - N ( sa l a ry C ( $ C ( $ ' ! : R ep l ac e W
ork ing Data F il e
. 2 J 7 & 2 2 & ! C ( - ( ? C ( & 1 ( !
? 7 # L 7 @ ) E R A G G R C ( & 2 O k & E : ( C ( 3 F i l e
O pe n
Da t a
A G G R C ( d e g re e sa l a ry 1 8 0.67 2 59 .8 0 3 42.50 ; " % K # " @ A g g re g a t e V a ri a b l e (s) % 9 * sa l a ry 1 $ *
L " ! < $ sa l a ry_ 1 1 N' … sa l a ry_ 2 R sa l a ry_ 1 ( ( 2 % . J . . / … 4 C ? L < $ sa l a ry_ 2 1 6
48
$ ( # I " ! ) & ( ( D
# ? . / :Se l e ct C a se s " ! - .10
. " ? 6 , #
E ? O 3 K / .
. 2002 – 1990 @ $ ' , " $ &
B: " 6 < 8 . . R 2002B1997 " $ E " ! - # L=
Se l e ct C a se s H
3 # Da t a
Se l e ct C a se s
- 2 E 6 ,
B: (
C ( " ! # - A l l C a se s - ;
49
2 I f C o n d i t i o n i s Sa t i sfi e d E - 2002B1997 " $ E " ! ? : ( 7 2 E 4 . H
3 # I F
& E-
# & ? $ ? K & 5 ' - H # & ? 9 ( E 8 # " ! E - (2002B1997) ( 6 " ! 2 O K
" ! ( 1 E . J 4 . fi l t e r_ $
2 J C ( 9
.
& E
1 # I * 2 Da sh e d 6 ,
B: ( @ " ! ( 0 E @
% - ; $ ( $ ! C ( C . 2 @ " ! - 3 !
- . * Se l e ct C a se s H
50
# U n se l e ct e d C a se s A re # F i l t e re d , J
B: 9 ( $ ; De l e t e d , J 2 E N @ " ! C . B a se d o n
, J N I - 2 (2002B1997 )" $ E " ! - -
@ " ! ; H
3 # R a n g e
" ! ( 1 E 6 ; C ( 9 fi l t e r v a ri a b l e
& E 2 T i me o r C a se R a n g e
. (13B8)
: 0 1
# I * $ ' " ! -
.1
2 % H $ ( # / # L= ! " ! ( 0 E / % L= B: ( ( N' X ) 1 . /
51
B: ( Se l e ct C a se s H
i f co n d i t i o n i s sa t i sfi e d
L 2
( . 9 ( $ ;
8 . 2 " ! 6 , F R a n d o m N u mb e r o f C a se s
.2
. " ! ( F - (" ! % 5 N' ) ( -
. Se l e ct C a se s H
# A l l C a se s , J 2 E " ! ) 1
C ( C a se s " ! & - ) 6 * * ? . / F : W e i g h t C a se s " ! F 6 , #
.3
.11
E ? O 3 K / / ? # ' ! N 3
. E " ?
/ - - N & $ - N ( ) @ # ( 6 - $ 2 E : 2
.SP SS Da t a Ed i t o r , , # " ( - % "
w e i g h t &
d e g re e
!
30
60
10
10
50
52
7 0
75
55
$ ?
;
<
: ( L( 6
. ? " ' 6 L
. ? " ' F
6 L
.1
.2
2 E 6 , 6 L .1 A n a l yz e De scri pt i v e St a t i st i cs F re q u e n ci e s 9 ( $ ; M e a n , J < (F re q u e n ci e s ? $ < $ < ) :
Frequencies Statistics DEGREE N V a lid M is s in g M e a n
4 0 6 5 . 00
: " 6 < < ? " ' w e i g h t 1 F
W e i g h t C a se s H
3 # Da t a
6 L
W e i g h t C a se s 2 E 6 ,
.2
: $ , 7 2 E 4 .
, , # 1 4 - 3 ' 8 - N ( ) w e i g h t 1 C ( " ! & 2 O K
& E
: 9 ( $ C F re q u e n ci e s ? 6 L
. ( Da t a Ed i t o r
F r e q u e n c ie s Statistics DEGREE N V a lid M is s in g M e a n
H
53
1 00 0 6 0. 00
# Do n o t w e i g h t ca se s , J 2 E C ( " ! F ) 1 : 3 ' .W e i g h t C a se s
" # # " < \ R o w
Data T ransf ormation Da t a ( ? " 9 ( $ &
. 6 , b
70 2 @
" ! 9 ( ! @
" 1 9 *
: ? 3 T ra n sfo rm % 2 I
" 1 L * ? . / F : C o mpu t e ?
. ( " & R * R $ ) I
: ( Da t a Ed i t o r , , 9 * * 2 . ( x2 x1 1 $ $ x1 x2 60 9 0 8 7 8 8 7 0 43 9 0 8 0 57 55 7 3 47 9 5 9 0 66 50 40 55 55 8 0 8 5 7 5 8 8 8 6 35 7 0 2 % # x2 x1 1 " ! ( * ) M e a n 6 L L( 6 H
54
3 # Transform
.1
: 2
: " 6 < 8 . . . X 1, X 2 ≥ 50
comp u te
2 E 6 ,
: $ , 9 ( 7 2 E 4 . comp u te variab l e
: " (
-%
. X2 X1 6 @ / 4 . Targ et Variab l e C 1 2
.-
.( X3 C 1 2 L - 2 Targ et Variab l e $ - $ 6 E - )
# typ e &
H
.
& 6 1I
2 F u nctions % M ean /
.L
& E 2 @ 9 ( $ X2 X1 / ( " 1
. 5 ' - H
3 # Typ e &
# F I / @ < % # M ean
L ab el & E - C 1 >
: ( 5 % L ab el
." .;
: - ;
- ) l ab el ( @ @ E X3 1 ( ) 6 * 7 ' : label - M ean(x1, x2) % ( & 120 1 $ 6
u se exp ression @ @ E X3 1 / N u meric exp ression . as l ab el
N & 1 # - nu meric 4 / 1 ( I # ! > -: t y p e " ( ( Y
comp u te H
55
. w id th 1 $ 6 > L # S tring
cases "! ) &
! .continu e & E ) !
# if E ( x1, x 2 ≥ 50 # "! L ) L ! if cases H
3 variab l e
incl u d e al l cases E "! # I
incl u d e if case satisfies cond ition E "! ) &
6 , $ * 2 ? E 2 E "! ) &
$ 6 , G
H
# O K
I
L -
$ C DF
•
$ 6 $ # @ & ? ! ( x 2 ≥ 50 x1, ) : $ , 7 if C ases H
& 2 I f C ases H
3 ; @ #
# continu e & E
x3 / - 1 # I * 2 ; L ! 9 ( $ 2 C omp u te Variab l e x1 60 8 7 70 90 57 73 95 66 40 55 8 5 8 8 35 9 ( $
•
x2 90 8 8 43 8 0 55 47 90 50 55 8 0 75 8 6 70 *
. . .
: ( Data E d itor 9 * ( x2 x1 1 ( 6 ) x3 75 8 8 8 5 56 93 58 68 8 0 8 7
. F S P S S # @ # ! " & $ : ' 0 1
2 1 # 8 . # ? " & 4 - 1 2 E ( E "! ! 9 ( $ ' # (T … t < & R 6 < & $ ) " &
8 . p arameters 2 H 6 < & , 1 2 % % 4 ? ( E : $ , # < &
56
CDFZ=CDFN O R M [Z]
CDFt=CDF.T[t,15]
CDFb i n o m =CDF.B I N O M [x , 10 , 0 .5 ] b i n o m i a l r .v .
n
p
t-d i s t. r .v .
d f
: . Deg rees of F reed om " $ : d f
. , ? 6 I $ : R and om N u mb er S eed ? : C ou nt ?
E K " L " ! # / - ? . *
4 - # "'
1 ; ! / 2 $ O L ; E "' . $ @ ) E "'
y2 8 3 7 1 1 10 7 6 9 1 6 9 3
# yes "
# ( Data E d itor # " $ * 2 ) y2 y1 1 D
57
.3
$ > ' 6 . $ $ 9 ( # . $ " 1
L 4 .
y1 1 15 14 9 1 4 6 11 15 9 6 20 16
.2
: 2
: $
25
22 8 5 7 7 # # 20 6 1 2 % ? " L 4 . y3 ; 1 # L= Transform
B: " 6 H 6 8 . . . 1
C ou nt
2 E 6 ,
7 2 E 4 . C ou nt O ccu rrence of val u es w ithin cases
H
3 : (
: ( L( 6 ;
1 $ * y3 / Targ et variab l e C 1 2 $ *
.-
9 ( " 1 - ) " 1 % y2 y1 1
.L
3 Define val u es & E / " L 2 E C D
."
.( ) C
. N u meric variab l e $ 6 9 * ( E 2 ( & - ) > K
2 J # 1، 6، 20 2 E $ J L= - ; Val u es to cou nt 2 E G # I A d d
1
H
: " 6 L 8 .
& E 2 1 E $ val u e ( $ 6 E 1 E $
•
E # I A d d & E 6 E $ val u e ( < E 6 E $
•
( $ $ 6 E 2 ( H $ - ) R ang e @ E # 20 E $
•
. # val u e to C ou nt $ 6 9 * E . # Val u es to cou nt % 9
: $ , 9 ( - 4 - 20 L R ang e
58
; . # Val u es to C ou nt % 9 * J # 20 Y # I A d d : (
& E 2
val u es to C ou nt H
$ ,
K & / , J % C . R emove & % 1 $ C hang e & - N ( cou nt occu rrence of val u es w ithin H
. Val u es to cou nt % # ?
9 * > ( C ontinu e & E
y1 y2 y3 1 C I ? . / # O K & E 2 cases 1 8 1 : Da t a E d i t o r y3 15 3 0 14 7 0 9 1 1 1 1 2 4 10 0 6 7 1 11 6 1 15 9 0 9 1 1 6 6 2 20 9 1 16 3 0 25 22 2 8 5 0 7 7 0 ; 1 2 % % $ (& ) cod e ) 6 * # ? . / : R ecod e ?
.4
@ 7 %
.
: & ? I " $ #
1 # ? . / : R ecod e into same variab l es ? . 2 E 1 2 - K 1 . / . J 2 % 1 2 E &
2 E . J 4 . sal ary 1 D : 2 sal ary : 20 16 95 8 8 65 53 35 46 90 22 30 28 51 60 8 5 % $ C od e & ) 6 * / L ( 6 . Data E d itor , , # 1 2 % "( - % : L L 1 2 %
= 1 2
59
' <
$ % # 24 49-25
74 B50
3
# 75
4 Transform
R ecod e
: " 6 < 8 . .
into same variab l es
2 E
: ( 7 4 . R ecod e into same variab l es H
3 #
9 ( 1 7 N ( ) % & 4 . sal ary 1 E H
.( & ) > K (
3 # 2 E & E 6 O l d and N ew Val u es & E
: 2 E 3 ' ; O l d and N ew Val u es
H 6 - @ E 2 % - @ % ) % & ) 6 * 2 E / : o ld
v alu e .( 2 E
.@ E N % - E 2 E ( 9 6 & / : n ew v alu e
$ * 2 rang e @ @ E ol d
val u e % # $ % # 24 9 ? $
( $ % # 24) ( $ E & $ val u e $ 6 E N ew
ol d and new
6 0
. ol d
H
new
: ( "
•
Val u e % #
•
% 9 * $ E & < # I * 2 # A d d ` & E
•
.1 /
3 ; / - < " E $ * 2 E 6 K
: ( val u es
: " & * # , J 7 N (
E $ - O l d Val u e % # E E $ - / , J # 1 C hang e & .N ew
F ; & &
O ld
. N ew Val u e % # @
% # / , J # C . R emove &
C ontinu e & E " $ * ) !
B: $ , 9 ( Data E d itor # sal ary 1 sal ary : 1 1 4 4 3 3 2 2 4 1 2 2 3 3 4 & ( $ Data E d itor E C & $ % S al ary ( ? 1 2 % - 4
C ( 2 - K C ( 3 2 2 E ( ? 1 4 4 . C ( - N ( R C od es & 1 & ) 6 * ? . / : R eced e into d ifferent variab l e ?
. 2 E
K 9 * & < < 7 / L ( ? 2 E 1 9 ( 3 < ^ 1 #
.>
. 1
& & @ . " L H $ # S al ary 1 & # L= : 2
. C ( 1 #
" 6 < C ( 1 9 * sal ary 1 & Transform
R eced e
into d ifferent variab l es
2 E
: ( 7 4 . R ecod e in to d ifferent variab l es H
2 - ( - / N u meric Variab l e
3 #
O u tp u t % 9 S al ary 1 $ E % %
& E < sal cat 2 ! 2 N ame # $ 6 E H 6 1
. 8 . = 2 ? 1 E 6 K C hang e
E 6 K @ E 2 E $ * 2 O l d and N ew
$ R ecod e into d ifferent variab l es H
6 1
Val u es & E
•
3 " 1 K 9 * & : (
H 6 ( 9 6 2 ) 1 ( E 2 E 3 ! : ' 0 1
.new val u e cop y ol d val u es ol d val u e A l l other val u es
s a la ry 2 0 16 9 5 8 8 6 5 5 3 35 4 6 9 0 2 2 30 2 8 5 1 6 0 8 5
R ecod e into H
Data # sal cat 2
s a lc a t 1 1 4 4 3 3 2 2 4 1 2 2 3 3 4
# C ontinu e E
1 C I d ifferent variab l es
: $ , # E d itor
(" 1 L ) categ oriz e variab l es ?
" $ 9 1 $ 2 E )
6 2
. /
C ? ( " 1 ) 1 2 H
.5 L( 6
sal ary 1 ( 4 9 * " 2 . * ' # categ ories
$ % 2 E L ) $ ? < # 1 2 E 1 2 % G
2 #
.( % 25
% 50 9 % 25 ) 1 2 E 2 2 % G
.( % 75 9 % 50 ) 1 2 E 3 2 % G
.( # % 75 ) 2 E 4 2 % G
Transform
: " 6 < (sal ary 1 ) H $ K 5 . / .
C ateg oriz e variab l es
2 E
: ( 7 4 . categ oriz e Variab l es H
3 #
.(
: ( Data E d itor 9 nsal ary 1 # I * 2 O K nsal ary 1 1 4 4 3 3 2 2 4 1 2 2 3 3 4
3 #
& E
. ! :
@ 7 %
A u tomatic R ecod e E ( &
1 E ( & # 2
.6
" 1 " ) ) 2 E 1 ( ( & - ) % ( & 2 -
1 ) name ( 4 1 ) sal ary 1 I C ( : 2
name A hmad S amer L oay M ahmood A yad Y assin S atar
: ( ( 4 &
sal ary 40 35 50 8 0 70 66 8 5
: " 6 < 8 . . . E ( & # L 1 & L( 6
Transform
2 E
A u tomatic R ecod e
# name sal ary 1 $ 0 2 E ; A u tomatic R ecod e H
N' (& ) 1 - 6 2 Variab l e
N ew
N ame %
rname rsal ary
$ * 2 ? K & 1 , J H 6 1 2 ( 1 -) $ *
. N ew N ame & E 2 N ew N ame & $ 6 # 1 2
•
-
R ecod e starting from L ow est val u e "
R ecod e starting from H ig hest val u e & "
H @ C - C ( ? $ ( L & " 1 & 2
. @ 1 C
6 3
: ( 3 Data E d itor 9 * 1 C I O K name sal ary A hmad 40 S amer 35 L oay 50 M ahmood 8 0 A yad 70 Y assin 66 S atar 8 5
rname rsal ary 1 2 5 1 3 3 4 6 2 5 7 4 6 7
5 . / " 1 L @ / @
& E
R ank C ases: ?
" 1 5 . / 6
.7
. Y - " 1 6 1 L ) 6 * . & L
reg ion E 6 g end er reg ion g end er sal ary 1 2 30 1 1 70 1 1 100 1 1 50 1 2 45 1 2 36 1 1 70 1 2 25 1 2 22 1 1 42 2 2 15 2 1 100 2 1 110 2 1 8 8 2 1 92 2 2 55 2 2 32 2 1 47 2 2 20
K sal ary
? " 1 4 C ( : 2
: Data E d itor # 3
? 1 N ) 6 * - D
" # I
Transform
g end er K
" # I
sal ary
. reg ionE 6
: " 6 < 8 . . C ases 2 E
7 4 . R ank C ases H
3 # R ank
: (
G end er 1 - Variab l es # S al ary N 5 O 6 * 4 . 1 $ 0 % E
# * 2 # G rou p ing Variab l es < " 1 # L 2 . ( reg ion . N L ) 6 S mal l est Val u e , - A ssig n R ank 1 to # B y
6 4
H
3 R ank cases H
# R ank Typ es & E > !
R ank L ( 6 > 7 R ank C ases:Typ es
9 * rsal ary 2 ( L 1 )
1 C I O K
reg ion g end er sal ary rsal ary 1 2 30 3 1 1 70 4 1 1 100 5 1 1 50 2 1 2 45 5 1 2 36 4 1 1 70 4 1 2 25 2 1 2 22 1 1 1 42 1 2 2 15 1 2 1 100 4 2 1 110 5 2 1 8 8 2 2 1 92 3 2 2 55 4 2 2 32 3 2 1 47 1 2 2 20 2 R eg ion " # I (; -R . ) G end er " # I
& 2 continu e & E
: $ # Data E d itor
sal ary 1 ( L ) 6 * 2 7 - 3 !
:" 3 '
& " 1 ( L ) 6 * ! 6 E # " 1 ( L ) 6 * G rou p ing
. ^ # 4 1 ?
L ) 6 *
< " 1 $ 9 * 1 L ) 6 *
. (2 1 ) .1 .2
< 4 1 $ S al ary 1 ( L ) 6 * H $ # Variab l es
6 5
R ank C ases H
# B y 5 . / # reg ion g end er . " 1
% 4 - ) ( ? 1 ( 2 E K "! ( L 2 3 D H
3 ; R ank
cases H
1
# Ties & E 2 ( " @ 1 (
.3
: @ 2 E ( " - 4 4 .
: , 2 E ( ? H 6 L G $ Val u e M ean L ow H ig h seq u ential 10 1 1 1 1 15 3 2 4 2 15 3 2 4 2 15 3 2 4 2 16 5 5 5 3 20 6 6 6 4 R ank C ases : Typ es H # / L > ? I
7 1 2 % % $ ) 6 * 2 ; ) 6 / : R ank
.4
. (
. 9 ? < & L 1 2 E L 6 : S avag e S cores
& ? > 9 ( 1 2 E 6 % / : F ractional R ank
.( 9 * & 4 - & - 2 # "! - ) "! #
. 100 # E L I
$ 5 . / 9 ( $ 2 : F ractional R ank as %
"! # & ? > $ "! # : su m of cases w eig hts . ( & - 2 # "! - )
) $ 9 6 < 9 * 1 2 % 2 E L ) 6 * 2 : N til es
2 E ( 1 ) 6 * 2 7 # (4 L ) 4N til es . 0 # ( & -
% 75 9 * % 50 2 E ( 3 % 50 9 * % 25 2 E ( 2 9 6 % 25 $ %
.H # # % 75 4
: > - - / " E : p rop ortion estimates
1 L 1 2 E ) 6 * 2 : B l om
(r − 3 8) ( w + 1 4)
$ r "! & - > $ w
6 6
* ;
1 L ) 6 * 2 : Tu k ey
( r − 1 3) ( w + 1 3) ( r − 1 2) w
1 L 9 6 : R anK it
/ r " / , / w
;
1 L 9 6 : Vand er w aerd en
r ( w + 1)
$ r "! & - > / w
;
x 1 ( "! ) 2 E ( H 6 L F I $
X : Variab l e 1 rx : R ank (simp l e) sx : S avag e S core nx : N til es rfr001 : F ractional R ank p er001 : F ractional R ank as % n001 : S u m of case W eig hts p x : P rop ortion E stimate (B l om)
- ;
6/7= 0.8 571
( (N' ) L
0.8 571*100= 8 5.71
(6-3/8 )/(7+1/4) =0.7759 P ro001 : P rop ortion E stimate (Tu k ey) (6-1/3)/(7+1/3) =0.7727 P ro002 : P rop ortion E stimate (R ank it) (6-1/2)/7 = 0.78 57 P ro003 : P rop ortion E stimate (Vand er W aed en) 6/(7+1) = 0.7500
( L
( L
( L
( L
( L
1 2 % @ / N ormal S cores L - : N ormal S cores
E stimated C u mu l ative " E $ E Z S cores E 6
@ . ? H 6 " - H "! @ / P rop ortions : ? H 6 N ormal S cores L $ $ (… R Tu k y R B l oom )
6 7
B lo m
T u k e y
R a n k it
V a n d e r W a e d e n
P rop ortion " E 9 ( ! B l om 1 N ormal S cores L - N' "! @ / 1 . / 2 % - ; ( p x 1 ) B l om 1 E stimates
C u mu l ative p rob ab il ities
( "! ! ) 2 E 5 . ( E Z E 6 < & 1 2 % - 6 6 < & ( I DF 2 2 E 6 , Transform
C omp u te
9 ( $ ; I DF .N O R M A L (p x, 0, 1) ( ( 4 4 C ( 4 . 5 ' - $ # nx 1 2 % K
: C reate Time S eries & $ '
- 2 ? & " # $ ' 1 2 % @ / Time S eries & ( (
.8
? $ ' & ( ( ) , * ( % . - , ? Data Define Dates * $ @ $ ' & ( ( 9 ( " ( D ) * # c L=
" 6 R M oving A verag es 6 ? R Differences H B: I . l ead fu nctionR l ag
& " 1 R ru nning M ed ians
O # , 17 $ ' & ( @ & - , " $ tv 1 * D
: 1 $
H # $ # L= ( Data Define Date ? & ( ( ( T ) , * 2 ) year_ 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2003 2003 2003
6 8
. 1 month_ d ate_ 1 J A N 2002 2 F E B 2002 3 M A R 2002 4 A P R 2002 5 M A Y 2002 6 J U N 2002 7 J U L 2002 8 A U G 2002 9 S E P 2002 10O C T 2002 11N O V 2002 12DE C 2002 1 J A N 2003 2 F E B 2003 3 M A R 2003
. 9 ? Differences tv 274 207 255 350 38 2 38 3 351 268 38 0 409 445 455 460 48 2 449
2003 2003
4 A P R 2003 5 M A Y 2003
H
3 #
38 9 398
Transform
: " 6 < 8 . .
C reate time series 2 E
8 . N ew variab l es $ 6 # tv 1 2 $ 0 2 E ; C reate time series . ( 9 ? " % 4 - ) ( O rd er Difference t v _ 1% &
t v # $
o rd e r
( ? 1 2 9 ? L @ / 1 ( I # ! 2 ! * .( tv_ 1 7 - 4 -) ( ( 2 % 7 ( ( u nd erscore )
year_ 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2002 2003 2003 2003
6 9
: ( Data E d itor 9 * tv_ 1 2 month_ d ate_ tv tv_ 1 1 J A N 2002 274 . 2 F E B 2002 207 -67 3 M A R 2002 255 48 4 A P R 2002 350 95 5 M A Y 2002 38 2 32 6 J U N 2002 38 3 1 7 J U L 2002 351 -32 8 A U G 2002 268 -8 3 9 S E P 2002 38 0 112 10O C T 2002 409 29 11N O V 2002 445 36 12DE C 2002 455 10 1 J A N 2003 460 5 2 F E B 2003 48 2 22 3 M A R 2003 449 -33
1 C I O K
E
N tv
2003 2003
4 A P R 2003 5 M A Y 2003
38 9 398
-60 9
@ K # ( ? 1 % @ / & @ # # H 1 % -
0 1 .1
H 4 - 1 4 " . * E @ ( ( ? 1 % 7 N 6 1 / tv 9 ? H 1 / tv ∗ ) tvt∗ = tvt − tvt −1 $ , . * - . 9 ? # @ E % H 1 . ( & @ $ t ( ?
N! 9 ? H 1 9 ( H 6 H J # 2 4 H "
. 9 ? # E % H 1 . ( ? 2 E
& E 2 N ame # 2 ! H 6 tv _ 1 H 1 2 - 1
.2
F u nction # 2 E F u nction > 1 . C hang e . O rd er 1 2 E 6 K C hang e & E 2 E
3 = c & * # M oving ( year_ 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 & (
A verag es 6 ? $
.S p an @ $ 6 E L( 6 6 E # 2 5 ! N
2000B1990 " ( P rod u ct M E & ( ( 9 ( 4 C ( d ate_ p rod u ct 1990 50.0 1991 36.5 1992 43.0 1993 44.5 1994 38 .9 1995 38 .1 1996 32.6 1997 38 .7 1998 41.7 1999 41.1 2000 33.8 ( ( C entered M oving A verag es & 6 ? L L( 6
C reate H
7 0
: ( ' = ? 3 ) 2 2
: " 6 < 8 . . . S p an=5 @ $ 6 -
3 # Transform
C reate Time series 2 E
: 9 ( 7 4 . Time series
" 6 $ Data E d itor 9 P rod u c_ 1 2 J year_ 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 7 - 3 ' (S
1 C I O K
& E
: ( p rod u ct ( ( (
d ate_ p rod u ct p rod u c_ 1 1990 50.0 . 1991 36.5 . 1992 43.0 42.6 1993 44.5 40.2 1994 38 .9 39.4 1995 38 .1 38 .6 1996 32.6 38 .0 1997 38 .7 38 .4 1998 41.7 37.6 1999 41.1 . 2000 33.8 . p an @ $ 6 $ n ) n/2 / ( ( # @ E 2 E - ;
( 5= @ $ 6 - # ) 8 6 L . ? ? 8 2 M1 =
50 + 36.5 + 43 + 44.5 + 38.9 212.9 = = 42.6 5 5
: (
36.5 + 43 + 44.5 + 38.9 + 38.1 201 212.9 − 50 + 38.1 = = = 40.2 5 5 5 @ $ 6 # L ( 6 E 8 6 $ E ; M2 =
H 6 L 8 6 J # sp an is even
$
# U ncentered M eans & = " 6 M & $ 6 L 2 % 4 6
p rod u ct
50.0 36.5 43.0 44.5 38 .9 38 .1 32.6 38 .7 41.7 41.1 33.8
7 1
& @ $ 6 # - 4 #
4 & =
. .
. .
43.500 40.725 41.125 38 .525 37.075 37.775 38 .525 38 .8 25
p rod u ct_ 1
% 6 S p an=4 8 6
42.113 40.925 39.8 25 37.8 00 37.425 38 .150 38 .675
. ( S p an = 4 - # )
R ep l ace M issing Val u es @ E 2 E E
* L ( - H 6 7 @ E N - " 1 D
.9
@ E 2 % -
. 5 . / S P S S # ; @ E E E 5 . / # L : $
: ( E % income 1 4
.
.
in c o m e 9 5 10 0 11 12 0 10 0 14 0
: " 6 < 8 . . . 1 . E E E L( 6 Transform R ep l ace M issing Val u es - 2 E : ' ( ) *
R ep l ace M i s s i n g V a l u e s H
Method
3 #
14 5 14 7 15 0 16 6 17 0 19 0 2 10 19 9 2 15 2 17 2 30
@ / 1 ( I # 2 - ) 6 0 2 E ;
( ( 2 % 7 ( ( u nd erscore )
N ( ? 1 2 9 ? L
. C hang e & E 2 N ame # 2 ! 2 ! . / 1
: $ Q 7 2 E E > - - M ethod # ; @
. & ( ( ( ( 6 @ E 2 E E 2 : S eries M ean .1
2 E 6 9 ( ! @ E E E 2 : M ean of N earb y P oints .2
. @ E E $ - 9 ( - 6 L # @ 2 E $ 4 . S p an L
. @ 2 E ( 6 9 ( E : M ed ian of nearb y p oints .3
. @ E 2 E E # 6 $ ! L ( - : l inear I nterp ol ation .4
( P red icted Val u es O 2 E @ E 2 E E : l inear trend at p oint .5 ( ( N % . J 4 . ($ E 1 ) 9 ( ( 1 ) @ # ( ( 2 %
. n 9 * 1
. E # M ean of nearb y p oints L ( ? %
: I E # ( @ 2 E $ : S p an of nearb y p oints
7 2
. @ 2 E : N u mb er
$ $ @ % 8 / 7 - . / E # ( ( 2 % # $ : A l l . & ( ( # @ E 2 E #
. S p an =2 2 $ . / #
2 J 1 C I R ep l ace M issing Val u es H
# O K
& E
: ( Data E d itor % 9 income_ 1
income 95 100 11 120 100 140 . 145 147 150 166 170 190 210 199 . 215 217 230
7 3
income_ 1 95.0 100.0 11.0 120.0 100.0 140.0 133.0 145.0 147.0 150.0 166.0 170.0 190.0 210.0 199.0 210.3 215.0 217.0 230.0
: 7 + .
+ , -
(100 + 140 + 145 + 147) / 4 = 133
.1
.2
T a l l Tall 8 0 8 4 7 1 7 2 3 5 9 3 9 1 7 4 6 0 6 3 7 9 8 0 7 0 6 8 9 0 9 2 8 0 7 0 6 3 7 6 4 8 9 0 9 2 8 5 8 3 7 6 6 1 9 9 8 3 8 8 7 4 7 0 6 5 5 1 7 3 7 1 7 2 9 5 8 2 7 0 3 3 3 7 3 2 4 1 4 4 4 9 4 7 5 0 5 9 5 5 5 3 5 6 5 2 6 4 6 0 6 6
7 4
D
D e s c r i p ti v e S ta ti s ti c s Frequencies ( 1 4 )
L 1 % $ D D
? . / $
< " " " , & K E D
. " 6 6 : 1 $
" @ E 6 E " N 80 $ 6 - $ Tal l 1 D
< " / , " L # F req u encies ? 2
: " 6 L 1 . K E
- 2 E 6 , A nal yz e Descrip tive S tatistics F req u encies $ , 9 ( 3 4 . F req u encies H 3 # K & 5 E H 6 Variab l es % # Tal l & E 2 (
, J 4 $ D
1 $ *
9 E # ) ?
: - ;
: Display frequency table
L " , O D
D
% S tatistics H
. 7 <
: S tatistics
3 5 E R
: ( D
( " , O : - ;
B oxp l ots 6 6 < ) p ercentil es " Q u artil es " $ , P ercentile V alues
% . ( L ! E 6 $ K $ ( 1 B 6) # " "(
< # 2 % L N' $ ? . R R K R $ ?
& $ P ercentil es $ - $ 6 9 * 1 2 % # I * 2 # A d d
& E 2 P ercentil es
. & R emove & % 1 C hang e
" 9 * " 2 E 2 E # C u t p oints for E q u al
G rou p s -
. " , K E D
: Dispersio n
. $ % $ 6 #
. & & K E D
:C entral T end ency
. F 6 ) ! $ , < & K E D
: Distributio n
2 E S P S S J # Val u es are g rou p mid p oints < , J # :3 ' " ( " & $ 1 " - P ercentil es Val u es M ed ian L … P ie R B ar " 6 6 D
: H
.
: ch art
3 5 E : fo rm at
: - ;
- val u es 2 E L N & - N 4 $ # " / , L : O rd ered by . 2 E L 4 L $ . / # C ou nts "
7 5
variables : Multiple Variables : " # $ F req u en c ies !
. # % " ! & % $ ' ( . # # # % $ ' (
) : C o mp are variables
) :O rg an iz e o u t p u t by variables
. . + , - #
% " + # / 0 - :supress tables w ith m o re th an
c ateg o ries
. 0 # 12 ) 3 , 3 4
: 5 , 6 F req u en c ies !
O K
4 3
Frequencies Statistics TALL N M e a n S td . E rro r M e d ia n M o d e S td . D e v ia S k e w n e s s S td . E rro r K u r to s is S td . E rro r M in im u m M a x im u m S u m P e r c e n tile
V a lid M is s in g o f M e a n tio n o f S k e w n e s s
s
o f K u r to s is
1 5
2 5 50 7 5 9 0
56 0 6 8 . 16 2 .2 9 7 0. 00 7 0 17 . 17 - . 3 14 . 3 19 -.6 3 9 .6 2 8 3 2 9 9 3 8 17 3 2 . 00 3 4 .7 0 55. 2 5 7 0. 00 8 1. 50 9 1. 3 0
Q u a r tile s ( 2 5 ,5 0 ,7 5 ) P e r c e n tile s ( 1 ,5 ,5 0 ,9 0 )
: 7
( 9 0 ) ! # : V alid .
76
9 0 # : Missin g
TALL
V a lid
32 33 35 37 41 44 47 48 49 5 0 5 1 5 2 5 3 5 5 5 6 5 9 6 0 6 1 6 3 6 4 6 5 6 6 6 8 7 0 7 1 7 2 7 3 7 4 7 6 7 9 8 0 8 2 8 3 8 4 8 5 8 8 9 0 9 1 9 2 9 3 9 5 9 9 T o ta l
F re q u e n c y 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 2 1 1 1 1 4 2 2 1 2 2 1 3 1 2 1 1 1 2 1 2 1 1 1 5 6
P e rc e n t 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 3. 6 1. 8 3. 6 1. 8 1. 8 1. 8 1. 8 7 .1 3. 6 3. 6 1. 8 3. 6 3. 6 1. 8 5 .4 1. 8 3. 6 1. 8 1. 8 1. 8 3. 6 1. 8 3. 6 1. 8 1. 8 1. 8 10 0 . 0
V a lid P e r c e n t 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 1. 8 3. 6 1. 8 3. 6 1. 8 1. 8 1. 8 1. 8 7 .1 3. 6 3. 6 1. 8 3. 6 3. 6 1. 8 5 .4 1. 8 3. 6 1. 8 1. 8 1. 8 3. 6 1. 8 3. 6 1. 8 1. 8 1. 8 10 0 . 0
C u m u la tiv e P e rc e n t 1. 8 3. 6 5 .4 7 .1 8 .9 10 . 7 12. 5 14. 3 16 . 1 17 . 9 19 . 6 21. 4 23. 2 25 . 0 26 . 8 28 . 6 32. 1 33. 9 37 . 5 39 . 3 41. 1 42. 9 44. 6 5 1. 8 5 5 .4 5 8 .9 6 0 .7 6 4. 3 6 7 .9 6 9 .6 7 5 .0 7 6 .8 8 0 .4 8 2. 1 8 3. 9 8 5 .7 8 9 .3 9 1. 1 9 4. 6 9 6 .4 9 8 .2 10 0 . 0
. t all 2 ; < 3 ! % 1 2 # % $ 6 =
77
? # % 3 0 ! / ! & > (
Descriptives ( 2 4 ) 3 0
. z sc o res ) % (
S P S S 5 1 D at a E d it o r , A x1, x2, x3 % @ # x1 x2 9 0 50 12 7 0 52 15 56 55 19 6 5 6 0 22 8 5 6 5 20 6 0 6 9 57 50 7 5 6 2 51 8 5 An aly z e
D at a C
: % . ? 1 D esc rip t ives 1 0 ! > B ( D esc rip t ive st at ist ic s
D esc rip t ives
. $
: # $ C " 3 D 1 1 + D esc rip t ives !
2 #
x3
, 6
: 7
x−x ) % @ & : S av e stan d ard iz ed v alues as v ariables s . ? 1 ( ) $ E 3 E d it o r
: !
78
3
, 6 F 3 : O ptio n s
C " 3 # ) D isp lay
O rd er 1 G 0 ! % $ ' 7 : % ; % " 0 ! > (
variables % # " ; 0 ! > (
3 ;
) : V ariable L ist
. D esc rip t ives !
. % " 1 H ; ; 0 ! > (
. % " 1 . I + 3 ! ; ; 0 ! > ( . % " 1 . I 4 ; ; 0 ! > ( : B (
D e s c r ip tiv e s
) D esc rip t ives !
) : Alp h abet ic
) :Asc en d in g mean s
) : D esc en d in g mean s O K
4 3
Descriptive Statistics N
X 3 X 2 X 1
V a lid N( lis tw is e )
5 5 1 3 5
M in im u m 1 2 .0 0 50 50 . 0 0
M a x im u m 2 2 .0 0 6 5 9 0 .0 0
M e a n 1 7 .6 0 0 0 56 . 4 0 6 7 .3 0 7 7
S td . D e v ia tio 4 .0 3 7 6 .1 1 3 .2 1 8
variables % ; ; 9 0 ! % $ ' ( : " D at a E x1 9 0 7 0 56 6 5 8 5 6 0 . 6 9 . 57 . 50 . 7 5 . 6 2 . 51 . 8 5 .
79
1
n 3 6
3 7
d it o r C A % " ) % @ A J D esc rip t ives ! x2 x3 z x3 z x2 z x1 50 12 -1.38 7 -1.0 4 8 1.7 17 52 15 -.6 4 4 -.7 20 .20 4 55 19 .34 7 -.229 -.8 55 6 0 22 1.0 9 0 .58 9 -.17 5 6 5 20 .59 4 1.4 0 8 1.338 . . . -.553 . . . .128 . . . -.7 8 0 . . . -1.30 9 . . . .58 2 . . . -.4 0 2 . . . -1.234 . . . 1.338
Pivot Tables
S P S S
Pivot Table ( 1 – 5 )
$ $ , 6 , " # S P S S 5 1 % # 6 )
= 3 9 ! 1 + # # ) 0 5 V iew er : %
. R o w s H 0!
.1
. C o lu mn s 9 3 . L ay ers % 1 .
+ - < 0 !
.2
+ , " F = 3 % + # + + @ >
.3
7 " 3 0 # + # . , < % 1 . + 2 > ) 1 9 3 % # F E D % 1 . 9 3 J H 0 ! ; 9 3 A
( @ ) # % 1 . 9 3 H 0 ! 1 ; K S P S S 5 1 )
5 1 # J 0 , ! 1 (D 1 9 3 A ) # 9
, K 1 0 # 1 2 <- , ! ;" . S P S S # D 1 $ , E xc el . <= 1
# L # ) 0 S P S S
E d it P ivo t T a b l es ( 2– 5 )
V iew er $ $ F 1 + # L
9 ! > 4 1 # . P ivo t T ables E d it o r
# C " 3 9 3 % ) / 7 ; " . " ) An aly z e D esc rip t ives
S P S S P ivo t T able O bj ec t
E d it
. + : 1
C ro sst abs 5 #
.S P S S V iew er $ $ , 6 ( ? 1 # ! 0 # # #
TREAT * RECOVER Crosstabulation Count
T R E A T T otal
8 0
a b
a1
R E CO V E R 8 3 1 1
b1
2 9 1 1
T otal
1 0
1 2 22
: % . ? 1 F = 3 # L
. D " ) 0 #
9 ! , 6 - P ivo t
P ivo t in g T ray s + # 2 . $
: " P ivo t in g T ray s
5
5
C o lum n ic o n
L ay er ic o n
C o lum n tray
L ay er tray
R o w ic o n
R o w tray
: = ) 1 + #
.# , T reat % H ! (% ) C " 3 + H 0 ! !
.# , R ec o ver % ) (% ) C " 3 + 9 3 !
9 1 . # 1 . (% ) C " 3 + L ay ers % 1 . !
E xp ec t ed 2 - # ) 2 # 1 . O bserved 9 $
.1
.2
.3
# 7 . (? 1 # ! 0 1 # # ; " . ) 1 5 2 6 = ? )
1 . M 9 (9 3 H 0 ! ) ) 1 % 1 . 3 9 1 3 D E 1 # P ivo t in g
. " )
" 1 1 % 1 . 9 3 H 0 ! <= 3 , 6 A & 1 :
? ) 3 R ec o ver ) , 6 A " ) 5 <= # 0 C A ; ? t ray s . # 0 I ;
: (# # ) 0 ) 1 ) . 1 > ) 1 H 0 ! 1 9 3 # 1 1
4 1 ) ! P ivo t
C H ! ; P ivo t in g
T ran sp o se R o w s &
T ray s 9 !
. H ! !
C ) ; > "
C o lu mn s + # 2 . $ : . : # . # 5
TREAT * RECOVER Crosstabulation Count
R E CO V E R T otal
8 1
a1 b1
a
T R E A T 8 2 1 0
1 : C .
b
3 9 1 2
T otal
1 1
1 1 22
T ray s H ! !
P ivo t in g
C (T reat ) ) " A F = 3 #
: # , 6
TREAT * RECOVER Crosstabulation Count R E CO V E R
a1
T R E A T
b1
T otal T R E A T T otal T R E A T
T otal
T otal
a b
8 3 1 1 2 9 1 1 1 0 1 2 22
a b a b
( > 4 1 F 1 D " ) 0 ) 1 )# " " ! % 3 & N A : .S P S S V iew er $ $ . $ P ivo t
)
An aly z e
D esc rip t ives
R eset P ivo t s t o d efau lt s
C ro sst abs 5 #
: 2
.S P S S V iew er $ $ , 6 ( ? 1 # ! 0 # # ; " . "
TREAT * RECOVER * GENDER Crosstabulation Count G E N D E R f
T R E A T
m
T otal T R E A T T otal
a b a b
R E CO V E R a1 b1 2 1 3 6 2 8
1 4 5 1 5 6
T otal
3 5 8 7 7 14
: " # , P ivo t in g T ray s , 6 9 3
% 1.
(R ec o ver )
(S t at ist ic s )
H 0!
(G en d er )
8 2
H 0!
(T reat )
; . T reat " M G en d er " A H 0 ! " 6 =
G en d er ; 1 E f 7 O M m " A 1 . K 7 1 #
1 . !
L 1 ! % 1 . !
C H 0! !
1 . G en d er - C o u n t 1 . 9 1 . S t at ist ic s : "
(D " ) 0 ) 1 )# , 6 7 I M - "
N 1 m 1 . <= ) 1 . , 6 & f 7 O # , 6 1 .
: .
F = 3 # G en d er " f 0 " # 0 I D , : C . 1 . # = # ) , , % 1 . ! (# ) 1 . C # - % 1 . !
. m 1.
# 6 = : .
G en d er , ) M C
. ( 1 1 . C # = , = 1 . C # = , ) m
( # # ) 0 ) 1 ) S P S S
V iew er $ $ 2 . $ : .
1 D G o t o L ay e r C at e g o r y ! ( 1 . ) 0 f 7 & 1 . < (
, 6 P i v o t
G o t o L ay e r
) ( 1 . ) 0 D @ 1 (G e n d e r ) . m 1 . , @ 3 ;G
: # F = 3 . + 5
: (# # ) 0 ) 1 ) % . ? 1 + # 3 H !
/ 0 - :
# " a ) @ + H ! <= D 0 P 1 ;G H ! ) " 0 3
5
.<= F = 3
. ) H ! # " 6 C t r l +A l t +C l i c k 1 .
8 3
5
. a 0" ? 1 H ! 0 . V ie w
H id e
+ # 2
. L 0 D e l Q 0 H ! H
: % . ? 1 D 0 A 1 + H ! , 6 &
. T r e at " b ) 1 # " . ( ) 1 ) > 0 3 +
5
. V ie w
5
5
S h o w A l l c at e g o r i e s i n T r e at + # 2
+ # 2 J > 0 3 1 M .
V ie w S h o w A ll Book Marks ( 3 – 5 )
# % 1 . 1 . 4 + # " 0 " N @ 4 " ) % $ A 0 . ) H ! @
5
! ) 1 9 3 H 0 ! " ) ; : 3
x1, x2, x3 % = ! A % $ ' + # An aly z e d esc rip t ive st at ist ic s F req u en c ies Descriptive Statistics N
X 1 X 2 X 3
+ # @
13 5 5
M in im u m 50 . 0 0 50 12 . 0 0
M a x im u m 9 0 .0 0 6 5 2 2 .0 0
M e a n 6 7 . 30 7 7 56 . 4 0 17 . 6 0 0 0
S td . D e v ia tio n 13. 2 18 6 6 . 11 4 . 0 37 3
1 . > % $ ' $ ' # # 7 1 # 9 1 2 2
: (K 0 1 K 0 # ) "
: % . ? 1 Mean 1 . B o o k mark s " ) 9 $ A ? @
. S P S S V iew er $ $ # 1 + # # ) 0 1 2 : " Mean
8 4
# 1 . , 6 P 1 2
5
5
!
, 6 P i v o t
B o o k mark s S P S S V i e w e r $ $ 2
- H @ A d d 4 (<= me an - ) " ) 9 $ - # J B o o k mar k s : " bo o k mar k s !
5
, 6 # 0 C me an
C 1 . F N . mean 1 " ) 9 $ P Mean 1 . 4 2 K 1
. # $ + C # 9
: % . ? 1 (mean 1 . ) " ) 9 $ A (N ) (
)
. S P S S V iew er $ $ # 1 + # # ) 0 1 2
. B o o k mark s !
, 6 P ivo t
. !
B o o k mark s
# mean " ) 9 $ A .G O T O
. mean 1 . (
8 5
4
) 1 5 1
5
5
5
5
Explore
E x plore ( 1 6)
% 1 " ! A < ! " , % 1 ? # ) C 9 . ) E xp lo re ; "
. , ) ? % - # % . . 3
1 J 0 ! > J 9 $ J S c reen in g % 1 R
0 ) D 7
<= - < = ! & K A # - - " ) F # = % @ 0 ! & 6 % A T ran sfo rmat io n % 1 # C C H $ - 1 $ . ; ! 7 1 % = ) 1 >
(
J % 1 " ) 1 . ? 4 (
# ! 0 (1S4) 1 " ? 1 # > 0 ) T all (
0
0
:1 #
: % . ? 1 7 C " 3 E xp lo re H $ - 1 . (? 1
An aly z e
D esc rip t ive S t at ist ic s E xp lo re
. $
: " D 1 1 + E xp lo re !
, 6
: 7
. , " 3 ! & # " / ;G 9 ) (% ) :d epen d en t L ist
9 ) ! & # " / D . 1 B reak d o w n variable 4 :F ac to r L ist . (< - D @ + ) " 9 ! 1 ) % - ?
1 ) 4 . ) , 4 ) 4 # )
# 6 - . # # " 4 . #
< 3 . ! ? C , 4 1 T all 2 # " ; % - (
) 7 ) . 1 % - " H ) / . 3 A :L abel C ases by
" 3 / . 3 A H ) (
8 6
. < 4
( 2 ) % 1 H " , " "
. B o x p lo t . . 9 $ .
: !
, 6 F 3 :S tatistic s
: % 0 +
… % 9 9 % 9 5 1 G ; 9 : C o n f id en c e I n terv al f o r Mean
J S k ew n ess J S t an d ard
D eviat io n J Mean 0 ! / ! & % $ ' , 6 & :D esc riptiv es
R o bu st maximu m L ik elih o o d
.… K u rt o sis
4 3 4 " ! % : M-estim ato rs
K . D 1 # 2 4 4 3 9 ) 1 / . 3 A 7 E st imat o rs . T u k ey , H amp le, An d rew , H u ber % N ) 1
E xt reme 1 , $ ) 2 # 2 2 1 % - , 6 & :O utliers . S P S S 5 1 B
<= > 5، 10 ، 25، 50 ، 7 5، 9 0 ، 9 5 (
V alu es
) 1 : P erc en tiles
% - % 9 5 , " % - % 5 , 1 ) 2 5t h P erc en t ile . < 3 ! 2 ; ) 1
. C h ec k B o xD ? 1 $ E 1 % $ ' F B 1 G 3 : !
, 6 F 3 : P lo ts
: % 0 +
B o x plo ts .1
: / 4 = . . bo x –an d -w h isk er p lo t < @ D " 3 " .
: % # $
: B o x ! .
. < 3 ! , 1 3 ) % $ % 25 , 1 : Q1 # ? 1
8 7
3 % $ % 50 , 1 + 2 C % 1 : Q2 ? 1 . Med ian
. F < 3 ! , 1
. < 3 ! , 1 3 ) % $ % 7 5 , 1 : Q3 7 ? 1
Q3-Q1 , ! # . . h in g es
, " 3 " . ! = Q3 Q1
. . . I n t er Qu art ile R an g e ) 1 M 1 H ) h sp read D " 3 " .
Med ian . , ! #
. 9 $ G 2 # 2 C " 3 C ! : W h isk ers ! B % - . .;
: E xt remes . o u t liers 9 $ .B
. ! # . 1. 5 ! 3 ) 1 9 $ 7
: # $ ! # . 3 ! 3 ) 1 E x tre m e s
∗
o u tlie rs
Q 3 (h in g e ) w h is k e rs
M e d ia n Q 1 (h in g e )
hspread
L a rg e s t V a lu e (n o t o u tlie r)
s m a lle s t v a lu e (n o t o u tlie r) o u tlie rs
E x tre m e s
. (S k ew n ess/ - ) % $ ? 4 3 9 . ) . .
C " ? 4 E # ? 1 C ;2 . A " ? 4 E ! H !
(/ - ; ) C " ? 4 E 7 ? 1 C ;2 . A (/ - ; ) . ? 4 # # . 3 9 . ) W h isk ers # $
8 8
" ?4
/ # ) ?4
" ?4
: % B o xp o lt s
. ) # 4 ? " . . (
. . @
3 : F ac to r L ev els to g eth er
. 4 3 # # 9 ) % " . . (
3 :D epen d en t to g eth er
. B o xp lo t . . (
3 3 :N o n e
F ac t o r 4 ) K # + $ E #
. V ariable
D esc riptiv e .2
: % . . (
3
(N ) S t em # 4 C 2 + 2 . . : S t em-an d -leaf . . S
% . / 4 leaf / 4 S t em # ( 2 ) L eaf
% $ ) # + S t em # 4 C , E 5، 7 ، 12، 15، 16 ، 20 ، 21، 23، 30
. . 6 = % 10 , # # . % C 2 E V # + L eaf
1 # 9 3 E 1 # H ist o g ram
% , 1 0 h ist o g ram . . D 1 $
. 9 ) 1 . 3 % " ) > ) D E K S t em-an d -L eaf
VAR1 Stem-a n d -L ea f F r eq u en c y 2 . 0 3 . 0 3 . 0 1. 0
8 9
0
0
Stem &
0
0 0
Stem w i d th : E a c h l ea f :
. 1 . 2 . 3 .
P l o t L ea f 5 7
2 5 6 0 13 0
10 . 0 0 1 c a s e( s )
. + B (
)
: H i s to g r a m
+ B S;
. % 1 " )1 . ?4 1 - % . . #3 : Normality Plots with Tests.3
<"3 . ; ! 1 > L @ ). F a c to r V a r i a bl e
1 - : sp read v s. L ev el with L ev en e Test .4
4 K 3 - (<. $ ) <- ) - -
: 5 , 6 E x pl o r e
E x p lo r e
. ( 3 # #! 0 1
!
OK 4 3
Case Processing Summary
T A L L
N
V a lid 56
P e rc e n t 1 00. 0%
C a s e s M is s in g N P e rc e n t 0 . 0%
N
T o ta l 56
P e rc e n t 1 00. 0%
Descriptives T A L L
M e a n 9 5 % C o n fid e n c e In te rv a l fo r M e a n
L o w e r B o u n d U p p e r B o u n d
5 %
T r im m e d M e a n M e d ia n V a r ia n c e S td .D e v ia tio n M in im u m M a x im u m R a n g e In te r q u a r tile R a n g e S k e w n e s s K u r to s is
S ta tis tic 68.1607 63 .5 618
S td .E rro r 2 .2 9 4 8
72 .75 9 6 68.5 63 5 70.0000 2 9 4 .9 01 17.172 7 3 2 .00 9 9 .00 67.00 2 6.2 5 00 - .3 14 - .63 9
S ta nd a r d E r r o r
.3 19 .62 8
. I + ) E .
Me a n = 6 8 .16 07 , S td .De v i a ti o n = 17 .17 27 , S td . E r r o r = SD / n = 17.1727/ 56 = 2.2948 . ( ) 1 1 . I + ) H - ) + ) E . S td . E r r o r 7 : " B : µ " # $ % 9 5
X m t.0.025,55 * Std .Error ( t 2 C ) 0.025 #- t ?4 # B t 7
#= # C N S PS S Co m pu te V a r i a bl e !
5 1 9 $ 1 , n-1=5 5
I DF .T(p,d f ) Tr a ns f o r m
Co m pu te
I DF .T(0.9 7 5 ,5 5 ) = E D "3 d f = 5 5 p = 1-0.025 = 0.9 7 5 ) # # p 7 : " . " % 95 9 D "3 = t.0.025,55 2
90
U ppe r Bo u nd = 6 8 .16 07 +2*2.29 4 8 =7 2.7 5 L o w e r Bo u nd = 6 8 .16 07 -2*2.29 4 8 =6 3.5 7 : 9 ! C "3 9 ;
Pr ( 63.57 < µ < 72.57 ) = 9 5 %
% 95 + 7 2. 57 6 3. 57 1 ? . N 2 # + #- # Pr 7 7 F = 3 De s c r i pti v e s
:
# <= S PS S 5 1 % C "3 % )0 ) 4 A
J 1 D F o nt . N J De c i m a l s $ ) ; 3 J # S PS S V i e w e r
; ". # 1 K ..… 9 3 (
3 J Al i g nm e nt ?2
C "3 % ) / F o r m a t Ta bl e Pr o pe r ti e s (% (
3 $ $ )
) " C "3 H 2
)1 # ) " % 0 ! # # . F o r m a t Ce l l Pr o pe r ti e s
Trimmed Mean % & ' ( ) $ $
#0 % 5 C "3 % 5 H < 3 ! ; )1 B
. 9 $ 1 + 1 " . ;
; D + 2. 8 + % 5 2 56 ta l l 2 3 #
2 5 6 *0.9 0= 5 0.4
, H )1 1 #0 2 2. 8 C "3 2 2. 8 H
: " ; $ .
2 B 7 68.1607* 56 − 99 − 95 − 32 − 33 − 0.8 * 93 − 0.8 * 35 3455.5992 TrimmedMean = = = 68.5635 50.4 50.4 C = 33 32 2 C "3 = 95 99 2 56 N # 6 8 .16 07 *5 6 7 C "3 "! 2 . ; C "3 ") " ") = 35 93 : #
E x tr e m e s . " S PS S 5 1 % F Extreme Values
T A L L
H ig h e s t
L o w e s t
91
2
1 2 3 4 5 1 2 3 4 5
C a s e N u m b e r 28 38 6 16 23 43 41 5 42 44
V a lu e 9 9 .0 9 5. 0 9 3. 0 9 2. 0 9 2. 0 32. 0 33. 0 35. 0 37 . 0 41. 0 0
0
0
0
0
0
0
0
0
0
*+ , )
2 )1 C 3 Q1,Q2,Q3 2 = Qu a r ti l e s % )1
2 C 3 Pe r c e nti l e s % ( % )1 H ) # Bo x pl o t . . ? ) % 1 % 95 D " < 3 ! , 3 % 1 % 5 D 1 > + . … % 1 % 90 D " < 3 ! , 1 3 % 1 % 10 D 1 $ ) (25 th Pe r c e nti l e ) 25 #1 Q1 # ?1 <"3
(5 0th Pe r c e nti l e ) 50 #1 Q2 (.
) ?1
(7 5 th Pe r c e nti l e ) 7 5 #1 Q3 7 ?1
: % " 5 1 % # #
Percentiles 5
T A L L
2 5
P e r c e n tile s 50
75 9 0 9 5 W e ig h te d T A L L 34.7000 43.1 000 55.2 500 70.0000 8 1 .5000 9 1 .3000 9 3.3000 A v e r a g e ( D e fin itio n 1 ) T u k e y 's H in g e s
1 0
55.5000 70.0000 8 1 .0000
Q1= 5 5 . 2 , Q2= M e d i a n = 7 0 I n t e r q u a r t i l e R a n g e = 8 1. 5 - 5 5 . 2 = 26 . 25
W e i g h te d Av e r a g e
,
Q3= 8 1. 5
4 . . % ; )1 .
+ (n+1)*P = 5 7 *0.05 = 2.8 5 ! #) <= > ; ;" Me th o d
1 ? > 2 E D "3 . < 3 ! ; 3 2. 8 5 > ; # ! D "3 ( E x tr e m e
V a l u e s # ) 35 3 , 1 33 2 , 1
: " 1 I nte r po l a ti o n . # / E 1 2 C "3 5 th Pe r c e nti l e = 33 * 0.15 + 35 * 0.8 5 = 34 .7
D + ) E . C S k e w ne s s / - #) 1 6 = )1 . ?4 1 F 1 –0.314 / 0.319 = - 0.9 8
" 1 % # ( De s c r i pti v e s # )
. )1 . ?4 ?1 Ta l l E 1 " ) @ #1 E (-2,2) M @
–2
? 1
#2 1 % ( C ) <1 </ " ?4 ) , 2 1 1 %
. ( C ) <1 W / " ?4 ) ,
. )1 E 1 1 M-E s ti m a to r s 1 . " ! % 1 B
. 1 ; . . F ; 1 ; . 1 > 3 6 =
.ta l l " 3
92
M-Estimators H u b e r 's M - E s tim a to ra 69.1469
T A L L
a .T h e w b .T h e w c .T h e w d .T h e w
T u k e y 's B iw e ig h tb 69.3 8 5 9
e i g h t i n g c o n s t a n t i s 1.3 3 9.
H a m p e l's M - E s tim a to rc 68 .97 5 4
A n d re w s ' W a v e d 69.3 7 49
e i g h t i n g c o n s t a n t i s 4.68 5 .
e i g h t i n g c o n s t a n t s a r e 1.7 0 0 , 3 .40 0 , a n d 8 .5 0 0 e i g h t i n g c o n s t a n t i s 1.3 40 * p i .
? 4 ? 1 # D # . S te m -a nd -L e a f
S t em-and-L eaf
. . # B
. . # <1 <= 1 , )1 .
TALL Stem-a n d -Lea f
P l o t
F r eq u en c y
Stem &
4 . 5 . 7 . 9 . 1 4 . 9 . 8 .
3
0 0 0 0 0 0 0 0 0 0 0 0 0 0
4 5 7
9
Stem w i d th : E a c h l ea f :
6
.
8 .
. .
.
Lea f 2 3 1 4 0 1 0 0 0 0 0 0 0 0
. .
5 7 7 8 2 3 1 3 0 0 0 2 1 2
9 5 6 3 4 1 1 3 3 2 3
9
5 6 8 2 2 3 4 4 6 6 9 4 5 8 5 9
1 0 . 0 0 1 c a s e( s )
H is t o g ram - . /
+ )1 . ?4 C D H @ 2 # . + B # . .
. ( + B # #! 0 4 % . . #! ? ) . # <= 1 16
Histogram
14 12 10 8
Frequency
6 4
Std. Dev = 17.17
2
Mean = 68.2 N = 56.00
0
97
.5
.5
.5 87
77
.5
.5 67
57
5
5
.5
7. -9
07 -1
7.
5
-8
5
5
7. -7
5
7.
7. -5
-6
7.
5
-4
7.
-3
93
.5 47
.5 37
.5 27
TALL
B o x p lo ts
9 $ . 2 3 6 = D Ta l l " Bo x pl o ts . . # B
. ( / 3 ) <)1 . N 4 C $ <1 ! . .
?2
120
100
80
60
40
20
N=
56
TALL
1 % 1 " )1 . ?4 1 A L : N o rmal it y P l o t s w it h Tes t 3 1 % 1 " )1 . ?4 1 C @ & 1 Ko l m o g r o v -S e m i r no v
1
: % . . N o r m a l Q-Q Pl o t De tr e nd e d N o r m a l Q-Q Pl o t )1 . ? 4 " ")= % 1 - ) : ( , ) " 0 K o mo g ro v -S mirno v ) .1
) % $ E 1 " ) @ 1 7 N o n-Pa r a m e tr i c G o o d ne s s o f F i t Te s t
B C "3 # ! 2 . <)1 . N 4 - % 1 E 1 " " 1 @ 0 @
)1 . ?4 ?1
. ta l l % $ )1 . ?4 1 -
Tests of Normality
T A L L
K o lm o g o r o v - S m ir n o v a S ta tis tic d f S ig . .096 5 6 .2 00*
*. T h i s i s a l o w e r b o u n d o f t h e t r u e s i g n i f i c a n c e . a . L illie fo r s S ig n ific a n c e C o r r e c tio n
?4 # Fs (x) 7 D = sup FS ( x ) − FT ( x ) 1 - D ! & 7 x ? (# )1 . ?4 ) + 6 ?4 # FT (x) )" )
6 =
. ( ) ) n % ) - M 1 Ko l m o g r o v # D 6
M 1 ) @ # 1 2 C 3 P-V a l u e = 0.20>0.05 D= .09 6 #
. )1 . ?4 ?1 # . ?4 + % 5 - N o rmal Q -Q
94
P lo t
.2
?4 2 #1 C "3 "! % 1 9 $ # . .
; . # R a nk Ca s e s ? ) E x pe c te d Z S c o r e
, )2 )1 .
. ta l l " . . ( )2
Normal Q-Q Plot of TALL 3 2
Expected Normal
1 0 -1 -2 -3
20
40
60
80
100
120
Observed Value
? 4 % )2 . 1 # F = 3 . . . C "3 . #
C "3 C "3 % 1 " )1 . ?4 " ) % #1 + ) C "3 )1 .
<)1 . N 4 ? 1 ) % . … (1.5 ,1.5 ),(0,0),(-1.5 ,-1.5 ) # $
, . 3 9 )1 ? % . 9 1 <1 ? $ - # $ . E
C $ . 9 1 F = 3 # $ . $ . )1 . ?4 ?1 - % 1 ) . )1 . ?4 ?1 ta l l % $
D et rended N o rmal Q -Q
P lo t
.3
E . 9 1 % $ $ 3 D 1 . . " 1 1
. 3 % - M + C Q . + #' )1 . ?4 ?1 - % 1 5 . . (
) S PS S 5 1 . < )1 . N 4 - % $
C "3 "! % $ # 7 (
, De tr e nd e d N o r m a l Q-Q Pl o t
., )2 )1 . ?4 2 3 % $ " ) % # 1 + )
(-2,2) M @
? ( % 90 % 95 1 ) $ - # $ . 6 ) % P
. 3 (-2,2) M @
. L !
> ) % 1 " )1 . ?4
? Ta l l " % - 6 ) 6 =
F . .
< )4 N 4 # . D "3 ( % - % 90 ; + ) <1 . <)1 .
95
.2
Detrended Normal Q-Q Plot of TALL
.1
Dev from Normal
0.0 -.1 -.2 -.3 -.4
30
40
50
60
70
80
90
100
Observed Value
! "3 . 1 Ch a r t E d i to r L i ne a r I nte r po l a ti o n #= . . . . 1
. > 41 . . 1 D # + % -
% 1 " % = # 3 D E <)1 . N 4 - % $ E 1 B - : tall
96
8 0 8 4 7 1 7 2 3 5 9 3 9 1 7 4 60 63 7 9 8 0 7 0 68 9 0 9 2 8 0 7 0 63 7 6 48 9 0 9 2 8 5 8 3 7 6 61 9 9 8 3 8 8 7 4 7 0 65 51 7 3 7 1 7 2 9 5 8 2 7 0 3 3 3 7 3 2 41 44 49 47 50 59 55 53 56 52 64 60 66
factor A A A A A A A A A A A A A A A A A A A A A A B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B
. (3 # )1 . > 0 ) )1 . ?4 #) (
Tr a ns f o r m a ti o n
0 # . # C 22 1 3
Ta l l " 1 #
2
;G % 1 0 # . # 34 % 1 C # A ; F 9 C "3 3 # ! A #" /
+ E x pl o r e
% 1
!
F a c to r L i s t 2 (F a c to r D ) 4 : # $ 1 D 1
: " Da ta E d i to r % 1 ;
9 ! 1 B A 0 # (
D at a E dit o r ( * )
) % E E x pl o r e : " (
0 3
) . <= "
Extreme Values F AC T O R A
T AL L
H ig h e s t
L o w e s t
B
C a s e N u m b e r
1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
H ig h e s t
L o w e s t
:
Bo x pl o ts
6 16 7 15 22 5 21 9 19 10 28 38 23 30 24 43 41 42 44 45
V a lu e
93 92 91 90 90 35 48 60 63 63 99 95 92 8 8 8 5 32 33 37 41 44
120
100
80
60
TALL
40
20
5
N=
22
34
A
B
FACTOR
?1 3 )1 , 7 35 , 2 5 2 A 0 Ou tl i e r 9 $ 2 6 =
4 1 , 4 18 . 7 5 ! # . 3 3 # 1. 5 3 4 1 Q1=6 6 .7 5 C
L a be l 3 @ - 5 2 ( . ( E x pl o r e !
1 + >
L a be l Ca s e s by
) 4 ; 1 Bo x pl o ts . .
Test of Homogeneity of Variances
2 D A ) "
( 2 – 6 )
AN OV A 1 #" / 3 1 % @ 0
. % 2 C #! " + ' H K E . $ 3 0 (% = ) ) % ) . ( % ) . + ) % = ) E + 1 ! @ 0 1 3
" ) @ 1 7 L e v e ne Te s t 1 >
1 S PS S 5 1
G % 1 3 <1 G . 1 >
)1 " " 1 @ 0 @
# ) % = F , 1 1 >
@ Tr a ns f o r m a ti o n % 1 C "3 % = /
1 - + @
% ) 1 >
1
. $ % ) # )1 . ?4 . $ 3 C + ' K E ; F . ε ~ N (0, σ 2 ) )1 . ?4 D $ ) E . ( 0 7 % @ 0
97
. <@ ) # # )1 . ; ?4
>
% = 3 2 C # ! " ! $ 9 Bo x &
Co x Q 2
; ) ) , % ) . 1 2 = 3 C "3 9 ) . % 1 G
# ; 7 . ( 1 >
@ + ) H - 3 " .
; % 1 " Po w e r Tr a ns f o r m a ti o n % ) . G
C "3 . 3 % -
% = (
)1 F Po w e r > # 1-b "! % 1 # y 7 y1-b !
Trans f o rmat io n P o w er S S q u a re 2 1 N o ne S q u a re R o o t 1\2 0 L o g a r i th m R e c i pr o c a l o f S q u a r e R o o t -1\2 R e c i pr o c a l -1 . ) , 1 + # 2 % 2 C 1– Q
+ 1 >
<6
: #)- ) $
lo p b -1 0
1\2 1
3\2 2
> 6 =
# C % 1 B - 1 ) , 3 " % )
E 0. 329 1-b > E 0. 6 7 1 C # ") % 0 + >
E 1 + > V 1/2 1 2 0. 329 "! % 1 " )1 "
. 10 > I G " )1 . G " #) 1 - D <"3 G " "
1 >
1 A (< 1
. . . 1 1 >
S p read v s . L ev el w it h L ev en Tes t
Pl o ts !
, 6 + ) L
1 C @ A L e v e ne S ta ti s ti c s 1 (% ) ) % = )
# 7 (. 1 1 ? Bo x &
Co x ; " > 0 # ) S pr e a d –V e r s u s L e v e l Pl o t
M G
# . . , C "3 (L e v e l M ) % )" .
G
1 2 = 3 3 0 (S pr e a d 3 1 ) + ) C "3 I nte r Qu a r ti l e R a ng e )1 1 > >
C $ + (S l o p=0) . ? . . . E 3 1 M
3 1 2 = 3 ) Tr e nd 3 F . # . ? E K > 3 % )
D < "3 . < 0 % = # ; % 1 C "3 # / 4" % ) 1
3 % 2 # "3 (
# )1 . . 1 5 1 #) & 1 . (0 ! ;2 # + ) 1 >
12 ? A,B,C,D % ) )1 , % D "3 1 5 # # :3 Tr e a tm e nts O bs
98
.
1 2 3 4 5 6 7
: ) #
A 8 9 5
540 1020 470 428 620 760
B
C
D
1520 1610 1900 1350 980 1710 1930
43300 32800 28800 34600 27800 32800 28100
11000 8600 8260 9830 7600 9650 8900
8 9 10 11 12
. 4 9R .>
537 845 1050 387 497 670. 75
1960 1840 2410 1520 1685 1701. 25
18900 31400 39500 29000 22300 30775
6060 10200 15500 9250 7900 9395. 83
Me a n S td . De v i a ti o n 233.9 2 35 6 .5 4 6 6 8 8 .6 8 2326 .04 J 1 ) J ; #" ! J , $ "3 # , $ . : !
3 % 1 " ; # ? % ) 1 >
1 ; ".
7 ( 0 ! ) S PS S 5 1 Da ta E d i to r 9 C % 1 # A
# ) " 4 tr e a t ( ) ) % $ # d e pe nd : % . ?1 % 1 >
E x pl o r e
!
1 - . A,B,C,D % )
, 6 7 Ana l yz e De s c r i pti v e S ta ti s ti c s E x pl o r e
!
Pl o ts 4
. . ?1 ( Tr e a t 4
<6
: " D 1 )1 Pl o ts !
: # $ C "3 D 1 1 +
s pr e a d v s . L e v e l w i th l e v e ne te s t E x pl o r e
99
. $
<- ) + )
, 6 7 Po w e r E s ti m a ti o n : 2 3 : 9 . F H ,
A
3 # " Da ta E d i to r % 1 ; Treat A A
A A A A A A A
A A B B B B B B B B B B B C
B C C C C C C C C C C C D D D D D D D D
D D D
D
D ep en d 8 9 5 5 4 0 1 0 2 0 4 7 0 4 2 8 6 2 0 7 6 0 5 3 7 8 4 5 1 0 5 0 3 8 7 4 9 7 1 5 2 0 1 6 1 0 1 9 0 0 1 3 5 0 9 8 0 1 7 1 0 1 9 3 0 1 9 6 0 1 8 4 0 2 4 1 0 1 5 2 0 1 6 8 5 4 3 3 0 0 3 2 8 0 0 2 8 8 0 0 3 4 6 0 0 2 7 8 0 0 3 2 8 0 0 2 8 1 0 0 1 8 9 0 0 3 1 4 0 0 3 9 5 0 0 2 9 0 0D 0 E P E N D 2 2 3 0 0 4 0 0 0 8 6 0 0 8 2 6 0 9 8 3 0 7 6 0 0 9 6 5 0 8 9 0 0 6 0 6 0 1 0 2 0 0 1 5 5 0 0 9 2 5 0 7 9 0 0
1 00
. L e v e ne
! A . 1 1 >
! & 1 - .1
? 1 #= $ - M 1 2 = ) 1 .2
Po w e r Tr a ns f o r m a ti o n . (>
% 1 " = # N
G 1 + ) 2 = 3
: 5 C "3 #! OK 4. Co nti nu e 4
L ev ene + 4 $ ) 5 * # ( + 3 ) 3 .1
( 1 >
) ) @ 1 1 F B
L e v e ne ! A 1 ( 1 >
3 ) " 1 @ 0 @
Me a n . C "3 1 ! & F 2 7
C "3 1 ! O 1 1 ; $ .
Me d i a n .
.000<0.05 ) ≈ (p-v a l u e 3 )1 10. 7 8 3 % "1 .
" 1 @ 0 ' % 5 - M 1 ) @ ( 3 , A #! > 0 % 1 >
D "3
)1 "
. ; $ .
.
C "3 1 ! & 2 3
Test of Homogeneity of Variance
B a s B a s B a s w ith
e d o n e d o n e d o n a d ju s
M e a M e d M e d te d d
n
ia n ia n a n d f
B a s e d o n tr im m e d m e a n
L e v e n e S ta tis tic 10.783 10.6 2 1
d f1
3 3
10.6 2 1
3
10.779
3
d f2
4 4 4 4
15 .85 3 4 4
S ig . .000 .000 .000 .000
S p read v s . L ev el P l o t ) 5 * # ) 4 .2
1 >
3 " $ R
$ . . #=
" $ # % 1 # ; > C @ & 1
: . . (Po w e r e s ti m a ti o n )
9.0
Spread vs. Level Plot of DEPEND By TREAT
8.5 8.0 7.5 7.0
Spread
6.5 6.0 5.5
6
7
8
9
10
11
Level
* Plot of LN of Spread vs LN of Level Slope = .744 Power for transformation = .256
% )" .
G
1 2 = 3 $ - # $ ) F - #= L @ 7
% 1 # 4= > b=0.7 4 4 # , )1 M G
A,B,C,D # ) 0 > 1 ? 0. 256 > 2
) $ % = # C N 1 1-b = 0.25 6
# 3 = 1 F ( )1 " )1/2 > 1 ( G
K 0 ( + > 0 ! ;2 #) #@ 5 . ) + # 3
. ( 9 . ) Pl o ts !
1 #) % 1 # 1 "3 >
Tr a ns f o r m e d . 1 9 $ 1
Trans f o rmed $ ) * ) : * G % ) 1 C 9 . 5
L 1 ! Tr a ns f o r m e d E x pl o r e :Pl o t ! : # $ N a tu r a l L o g
C 9 ) 1 K
" ) Po w e r #
: ( " % G " ) % 1 . . , 6 OK 4 Co nti nu e
1 01
4 3
Spread vs. Level Plot of DEPEND By TREAT
.7 .6 .5 .4
Spread
.3 .2 .1 6
7
8
9
10
11
Level
* Data transformed using P = Slope = -.087
. 4 % 1 " $ - .
1 2 = )" 3 F 3 L @ 7
2 % 1 " 1 >
3 " $ /0 C $ . #
# ?. +
;2 1-b = 1.08 7 > E D "3 b=-0.08 7 # . 1 >
3 " $ )- % 1
: . . C "3 #! )1 "
18
Spread vs. Level Plot of DEPEND By TREAT
16 14 12 10
Spread
8 6 4
20
40
60
80
100
120
140
160
180
Level
* Data transformed using P = Slope = .078
)
;2 D + 0. 922 > E D "3 0. 07 8 + # 7
D "3 % = 3 = 1 5 % 2 . )1 1 % 1 " 1 >
. , + 3
1 02
C "3 3 - 1 . . 0 D E Pl o ts !
U ntr a ns f o r m e d
" 1 1
% G
1 ( I QR ) )1 M .
1 2 = ) 1 K ( % 1 # 1 ) "! Spread vs. Level Plot of DEPEND By TREAT
7000
: # $
6000 5000 4000 3000
Spread
2000 1000 0
0
10000
20000
30000
40000
Level
* Data transformed using P = Slope = .201
#) - . .
<"3 )1 M .
1 2 = )" 3 F 6 =
.% )" )1 M G
.
G
1 2 = ) # - D # N
!
( 3– 6 )
Opti o ns 4 1 9 0 <2 + % - )1 0 : O p t i o n s !
C "3 + % (% ) , " 1 )1 - #): E x c l u d e
, 6 E x p l o r e
: 7
C a s e s
L is tw is e
F a c t o r 4 D e p e n d e n t ) + 9 0 2
. @ -
% = + 9 0 2 , % - )1 : E x c l u d e C a s e s P a i r w i s e @ & 0 F , 5 (
. ) ! ; #)
3 " 0 4 9 0 #) : R e p o r t V a l u e s
: D a t a E d i to r $ $ % " % 1 (
1 03
0 1 L @
.
d e p 1 d e p 2 1 10 2 11 . . 4 13 5 14 . 6 . 7 8 A n a ly z e D
fa c 1 1 1 2 2 2 e s c r ip tiv e S ta tis tic s
E x p lo r e
0
1
: " ?1 E x p l o r e !
. F a c t o r L i s t C D " f a c 0
•
. D e p e n d e n t L i s t C , " d e p 2 d e p 1
5
5
•
. E x c l u d e C a s e s l i s t W i s e O p t i o n s 4
•
: , 6 O K 4
5
Case Processing Summary
D E P 1 D E P 2
F A C 1 2 1 2
N
V a lid 2 2 2 2
P e rc e 6 6 6 6 6 6 6 6
n t .7 .7 .7 .7
N % % % %
C a s e s M is s in g 1 1 1 1
P e rc e n t 33. 3% 33. 3% 33. 3% 33. 3%
N
T o ta l 3 3 3 3
P e rc 10 10 10 10
e n t 0 .0 0 .0 0 .0 0 .0 % % % %
Descriptives D E P 1
D E P 2
F A C 1
M e a n
S ta tis tic 1.50
2
M e a n
5.50
1
M e a n
10.50
2
M e a n
10.50
S td .E rro r .50 . . 1.50 . . .50 . . 2.50 . .
7 E x cl u d e Cases Listwise (# # 1 C " 3 ) %. ; 0 6-
Facto r List D epend ent List 2 % + 9 0 2 C " 3 + + ) 1
C " 3 2 1 C " 3 3 -1 fac 4 1 " d ep1 " . ; <= . ; 4 1 " d ep2 . 1 1 4 2 " 7 4 %- . ... 2 1 C " 3 3 -1
: " ; %. E E x cl u d e Cases Pairwise
1 04
Case Processing Summary
D E P 1 D E P 2
F A C 1 2 1 2
N
V a lid 2 3 2 2
P e rc e n t 6 6 .7 % 100. 0% 6 6 .7 % 6 6 .7 %
N
C a s e s M is s in g 1 0 1 1
P e rc e n t 33. 3% . 0% 33. 3% 33. 3%
T o ta l
N
3 3 3 3
P e rc e n t 100. 0% 100. 0% 100. 0% 100. 0%
Descriptives D E P 1
D E P 2
F A C 1
M e a n
S ta tis tic 1.50
2
M e a n
5.6 7
1
M e a n
10.50
2
M e a n
10.50
S td .E rro r .50 . . .8 8 . .50 . . 2.50 . .
1 1 2 1 %- ; 2 fac 4 d ep1 . 6-
. d ep2 " / $ > 0 7 6 4 %- ; 4 2 " d ep1 .
? E x pl o re !
Facto r List 2 fac
# ! V
Y E x cl u d e Cases Pairwise C " 3 / 1 &
# ! 7 " 9 ! 1 # 9 0 2 C " 3 %- ) 1 1 F
. 1 %. " C " 3
Descriptives D E P 1 D E P 2
M e a n M e a n
S ta tis tic 4.17 11.2 0
S td .E rro r .9 5 1.0 7
11. 0 2 d e p 1 " 7 6 5 4 2 1 %- . 4. 17
. d e p 2 " 7 5 4 2 1 %- .
C fac ? . Repo rt V al u es 9 0 " 9 1 # !
105
Repo rt V al u es $ E ? E x pl o re ! : 5 C " 3 # ! E x pl o re !
O K
Facto r List
4 3 . O ptio ns
Case Processing Summary
D E P 1 D E P 2
F A C . ( M is s in g ) 1 2 . ( M is s in g ) 1 2
N
V a lid 1 2 2 1 2 2
P e rc e n t 100. 0% 6 6 .7 % 6 6 .7 % 100. 0% 6 6 .7 % 6 6 .7 %
C a s e s M is s in g N P e rc e n t 0 . 0% 1 33. 3% 1 33. 3% 0 . 0% 1 33. 3% 1 33. 3%
N
T o ta l 1 3 3 1 3 3
P e rc e n t 100. 0% 100. 0% 100. 0% 100. 0% 100. 0% 100. 0%
Repo rt V al u es 2 1 <= ! D Fac 4 6-
Repo rt " ( # # 1 C " 3 ) %. ; . 9 0 " M issing E 1 %0@
: " V al u es
Descriptives D E P 1
D E P 2
F A C 1
M e a n
S ta tis tic 1.50
2
M e a n
5.50
1
M e a n
10.50
2
M e a n
10.50
S td .E rro r .50 . . 1.50 . . .50 . . 2.50 . .
7 E x cl u d e Listwise . > 0 1 2 . ; 9 0 ) 1 6=
. < 5 > 0 C " 3 " !
106
( 3 0!
Crosstabs
) 2 × 2 Tabl es 2 - # # 3 Cro sstabs # )
% $ ' ; ? ( 3 0!
) M u l tiway Tabl es 9 ) #
<= 1 . 7 1 9 1 9 , . ! & % 1 - # F , .1 -
. ! & % 1 - " 9 ) # 2 - # 3 A " 3 # ,
) @ a B = ) ) @ C @ " 9 $ 22 , 3 # # : 1 3 a1 / 0$ " 4 (
/ 0$ # reco v er treat K 3 1 ) b B = )
$ $ % 1 %" 2 7 O f " m ( treat a b b b a a b a b a a b a b a b b b a b a b
reco v er a1 a1 b1 b1 a1 a1 b1 b1 b1 a1 a1 a1 a1 b1 a1 b1 b1 b1 a1 a1 b1 b1
>
# g end er b2 / 0$
g end er m m m m m m m m m m m m m m f f f f f f f f
: " D ata E d ito r
: " ;" .
1 = - 1 ? reco v er treat 1 2 = ) " 2 #
.1
1 = - 1 ? reco v er treat 1 2 = ) " 2 #
.2
: % . ? 1 # ; " . 0
.1
.(
/ 0$ B = ) .) 1 ) 2 = 3 1 + . g end er >
107
;
Anal y z e
D escriptiv e Statistics
. # < 0!
Cro sstabs
: " D 1
+ Cro sstabs !
D # ) ;G
. # 9 3 D # ) ;G . $ E 3 1 . $ (
. $
, 6
: 7
+ @ : Row(s)
+ @ : : C ol u m n (s)
) : D i sp l a y C l u st e r e d b a r C h a r t s
. $ E 3 9 ) # 2 - # / 0 -: S u p r e ss t a b l e s
: " D 1
+ Statistics !
, 6 Statistics 4 3
: 7
. 9 3 3 H 0! = 1 - , " ch i-Sq u are ! A ; : C h i -S q a r e
; D <" 3 <) Pearso n Spearman .1 - " ) ; : C or r e l a t i on
108
H 0! = 1 3 1 Spearman .1 # ) ; Nu meric 3 " % 2
$ $ M easu re ) O rd inal ) O rd ered V al u es 1 2 3 9 1 3 9 3
Pearso n . 1 # ) ; (… ; J J ) " ) <= (V ariabl e v iew
Scal e 1 , 3 1 ) Q u antitativ e V ariabl es % 9 3 H 0! = 1 3 1 .I nterv al <@ , $ V ariabl e V iew $ $ M easu re 3
H 0 ! <= (.1 ) 2 = %= ) ) 1 ; F L : N om i n a l
(7 A J ) >
<= % 1 ; A 3 C @ & 1 G # 3 9 3
. (9 ! 1 J # ! J 1 ) 6
9 3 H 0 ! = 2 = %= ) ) 1 ; F L : O r d i n a l
. 1 %
9 @
> ) 1 2 = E ta ! A ; : N om i n a l b y I n t e r v a l
Categ o ries % 0 3 D # I nco me # # I nterv al Scal e R
. g end er >
#
" ) , 6- > 4 1 1 ! % ! A 1 C " 3 H ) K
No minal , ) No minal % # 9 3 H 0! < 6
. , 1
1 - Ch i- Sq u are ! A ; 1 0 ( V ariabl e V iew $ $ M easu re 3
.No minal V ariabl es - % " 2 = Ph i and G ramer’s v > ? = -
Cro sstabs !
o k Statistics !
Co ntinu e 4 3
: % C " 3 # !
TREAT * RECOVER Crosstabulation Count
T R E A T T otal
a1
a b
R E CO V E R 8 3 1 1
b1
T otal
2 9 1 1
1 0
1 2 22
Chi-Square Tests
P e a rs o n C C o n tin u ity L ik e lih o o d F is h e r 's E N o f V a lid
h iC o R a x a c C a
S q rre tio t T s e
s
u a re c tio n e s t
a
V a lu e 6.600b 4 .5 8 3 6.9 9 4 2 2
d f
1 1 1
A s y m p .S ig . ( 2 - s id e d ) .010 .03 2 .008
a . C o m p u te d o n ly fo r a 2 x 2 ta b le b . 0 c e l l s ( .0% ) h a v e e x p e c t e d c o u n t l e s s t h a n 5 . T h e m i n i m u m 5 .00.
109
E x a c t S ig . ( 2 - s id e d )
E x a c t S ig . ( 1- s i d e d )
.03 0
e x p e c te d c o u n t is
.015
@
/ 0$ 3 B = ) = + 9 3 3 H 0! = 1 " ) @ 1
, Ch i-Sq u are ! A 1 / 0$ B = ) 1 2 = 3 1 " " 1 @ 0
: ! ; 9 3 3 c H 0! 3 # r 7 (r-1)(c-1) 2 χ 2 = (Oi − Ei ) ∑ Ei 6. 6 ! & 2 % 2 ? 2 # Ei $ # Oi 7
1 2 = 3
+ %5 - M 1 ) @ (
C 3 p-v al u e= 0.010 < 0.05 2 .(
/ 0$ B = )
Symmetric Measures
N o m in a l b y N o m in a l
N o f V a lid C a s e s
P h i C r a m e r 's V
V a lu e .548 .548 2 2
A p p r o x .S ig . .0 1 0 .0 1 0
a . N o t a s s u m in g th e n u ll h y p o th e s is . b . U s in g th e a s y m p to tic s ta n d a r d e r r o r a s s u m in g th e n u ll h y p o th e s is .
C A $ p-v al u e =0.010 2 E
χ2 = n
6 .6 = 0.548 Ph i = 2 > 22
1 = - 1 - χ 2 ! A # ) 7 J % 5 - M 1 2 - ) . (r-1)(c-1)
Co ntinu ity Co rrectio n = Y ates L ! ; : 1 2 ( Oi − Ei − 1 / 2) 2 χ . =∑ ! ; 2 × 2 # + + Ei > , ) 2*2 2 - # ? # ) <1 G Ph i 2 > : 2 : 2 = ) r*c 9 ) # ; + Cramer Co efficient C 1 H ) C=
χ2 = N ( L − 1)
6 .6 = 0.548 22
# 9 3 H 0! 1 ! ) L ) # N 7 > 2 6= (r-1)(c-1) 1 = - 1 - χ 2 ! A # ) 7
. Ph i 2 - > <
) Co nting ency Co efficient # ) 1 H ) ; > K : 3 r*c # + ; (<0 Cro sstsbs:Statistics !
110
No minal
: 2 = )
χ2 = 2 χ +N
C=
6.6 = 0.480 6.6 + 22
1 = - 1 - χ 2 ! A # ) ) # N 7
F = 3 = %= ) " , 0 = - 1 P-V al u e 2 7 . (r-1)(c-1)
D ispl ay Cl u stered Bar Ch arts Ch eck Bo x $ E 5 . 0. 010 +
: .. .) Cro sstabs !
10
8
6
4
RECOVER
Count
2
a1 0
a
b1
b
TREAT
!
: 4
Cel l s 4 1 K Cro sstab # % (
) 1
.1
: @ + Co u nts
•
: % = @ + Percentag es
•
: % + + Cel l D ispl ay
!
, 6 7 Cro sstabs
. Oi $ 1 # = I 7 @ - : O bserv ed . Ei ? 2 1 # = I ; 1 : E x pected . H ! N ' ; 1 # = I : Ro ws
. ) N ' ; 1 # = I : Co l u mns . " N ' ; 1 # = I : To tal : % = @ : Resid u al s
.
Oi − Ei ? 2 $ 1 0 1 # = I : U nstand ard ised
•
C " 3 < ? 2 $ 1 0 1 # = I : Stand ard iz ed . D + ) E .
. . 3 + ) H - % 1 D 3 < 1 ) 1 > 0 : Ad j .Stand ard ised
!
111
Fo rmat 4 1 < 4 < 3 ! # H 0!
; : 5
Cro sstabs
Anal y z e
D escriptiv e Statistics
: % . ? 1 ; " . 0 Cro sstabs
: " D 1
9 . 1 H ) ( 1 .) Lay er 2 @
. $
+ Cro sstabs !
.2
, 6
g end er # A D 6=
# 3 D ) categ o rical V ariabl e + Co ntro l V ariabl e
treat 1 2 = ) " Cro sstabs # 7 ( f m 2 g end er "
m " D + 9 . 2 2 # > ; reco v er . f 7 O
: 5 C " 3 # ! Cro sstabs !
O K
TREAT * RECOVER * GENDER Crosstabulation Count G E N D E R f
T R E A T
m
T otal T R E A T
a b
a1
a b
T otal
R E CO V E R 2 1 3 6 2 8
b1
T otal
1 4 5 1 5 6
3
3 5 8 7 7 14
Chi-Square Tests G E N D E R f
m
P e a rs o n C C o n tin u ity L ik e lih o o d F is h e r 's E N o fV a lid P e a rs o n C C o n tin u ity L ik e lih o o d F is h e r 's E N o fV a lid
h iC o R a x a c C a h iC o R a x a c C a
S q u rre c tio t T e s e s S q u rre c tio t T e s e s
a re tio na s t a re tio na s t
a . C o mp u t e d o n l y fo r a 2x 2 t a b l e
V a lu e 1.742b .3 20 1.76 2 8 4.6 6 7c 2.6 25 5 .0 0 4 14
d f
1 1 1
A s y mp . S i g . ( 2- s i d e d ) .187 .5 72 .184
1 1 1
.0 3 1 .10 5 .0 25
E x a c t S ig . ( 2- s i d e d )
E x a c t S ig . ( 1- s i d e d )
.46 4
.286
.10 3
.0 5 1
b . 4 c e l l s ( 10 0 .0 % ) h a v e e x p e c t e d c o u n t l e s s t h a n 5 . T h e mi n i mu m e x p e c t e d c o u n t i s 1.13 . c . 4 c e l l s ( 10 0 .0 % ) h a v e e x p e c t e d c o u n t l e s s t h a n 5 . T h e mi n i mu m e x p e c t e d c o u n t i s 3 .0 0 .
112
. ) 1 2 = 3 3 Pearso n Ch i-Sq u are ! & p-v al u e 2 # = 6=
1 1 2 = 3 C " 3 ! & ' 7 & C @ " 1 1 ( C " 3 R
/ 0$ /
. %5 - M C @ "
2 × 2 N # Ch i-Sq u are 1 - %@ 0 M A
5 C H 1 - E - # = + # + E 1 5 3 # - ; Ei ? 2
# %100# = 5 3 # ? 2 6=
# " " 6
. 1 - 5 3 ; 7 &
Symmetric Measures G E N D E R f
N o mi n a l b y N o mi n a l
N o fV a lid C a s e s N o mi n a l b y N o mi n a l
m
V a lu e .467 .467 8 .5 77 .5 77 1 4
P h i C r a me r ' s V P h i C r a me r ' s V
N o fV a lid C a s e s
A p p r o x .S ig . .1 87 .1 87 .0 3 1 .0 3 1
a . N o t a s s u mi n g t h e n u l l h y p o t h e s i s . b . U s i n g t h e a s y mp t o t i c s t a n d a r d e r r o r a s s u mi n g t h e n u l l h y p o t h e s i s .
GENDER=f
GENDER=m
4.5
7
4.0
6
3.5
5
3.0
4
2.5
3
2.0
2
RECOVER
1.0
a1
1
a1
.5
b1
Count
a
TREAT
113
b
Count
RECOVER
1.5
0
a
TREAT
b
b1
Compare Means
Means ( 1– 8 )
C @ & 1 ) su bg ro u ps 4 ? " %. ; # " 0
H - J # J .
J 4 3 " %- 3 J N ) # M % $ '
Test o f %= ) " . E 1 ) 1 # " / <@ (Z … + ) . eta 2 - 1 Linearity
>
1
; C J B J A 0" ? 3 C ; . 16 % ? 4 1 # : : # $ C " 3 D ata E d ito r $ $ , A G end er
d eg ree 70 90 8 8 8 6 6 8 6 4 76 8 3 79 5 5 97 100 6 4 5 9 90 73
g ro u p A B A B C C B A B C B A C C A A
g end er Femal e M al e M al e M al e M al e M al e M al e Femal e Femal e Femal e M al e M al e Femal e Femal e M al e Femal e
+ ) H - %- 3 C J B J A 3 0 ? ; % . ;
S: % . ? 1 3 #
!
114
, 6 Anal y z e
Co mpare means
M eans . $
S: # $ C " 3 D 1 1 + M eans
S: 7
F E < 6 Respo nse V ariabl e 1 - 1 H ) ) : D epend ent List
# ) . I nd epend ent V ariabl e # 1 . D eg ree 1 " . %
! Treatments %= ) # ' # : I nd epend ent List
? # # . ANO V A 1 # " ; Stand ard
. 1 " . % 4 # ) + g ro u p 4
J No . o f Cases J M eans M eans !
O ptio ns 4
? ; , 1 ; " . % $ ' M eans:O ptio ns !
D ev iatio n
S: " ; ) 1 ! , 6 7 4
S: 5 , 6 O K
115
Co ntinu e 4
Report DEGREE GRO U P A B C T o ta l
M e a n 8 4 .0 0 8 5. 60 62 . 0 0 7 7 . 63
N
6 5 5 1 6
S t d . De v i a t i o n 1 1 .1 9 8 .4 4 5. 0 5 1 3 . 65
. 4 3 # ; D eg ree " 1 " . % $ ' ; D 6= : 2 #
% + ) H - %- 3 . ; ;" . 1 # % 1 > 0
9
% . > 0 ? 1 K 0 . " 9 ! 1 g end er >
; g ro u p ? ;
: # $ C " 3 M eans !
; 1 1 #
" ; 5 , 6 DEGREE * GROUP DEGREE GRO U P A B C T o ta l
M e a n 8 4 .0 0 8 5. 60 62 . 0 0 7 7 . 63
N
6 5 5 1 6
S t d . De v i a t i o n 1 1 .1 9 8 .4 4 5. 0 5 1 3 . 65
DEGREE * GENDER DEGREE GENDER F e m a le M a le T o ta l
116
M e a n 6 9. 0 0 8 4 .3 3 77. 6 3
N
7 9 1 6
S t d . De v i a 1 0 1 2 1 3
tio .2 .4 .6
n
5
3
8
3 #
; d eg ree " + ) H - %- 3 . ; ;" . 1 # > 0
1 . 1 K 0 . C J B J A 3 0 ? # # (7 A J ) > @ 1 . g ro u p @ C 1 . M eans ! : # " ; M eans !
Lay ers
, 6 3 % 1 . F # 3 g end er
. Lay er1 C 1 . I nd epend ent List C g ro u p #
. Lay er2 1 . C # = I nd epend ent List C " 3 Nex t 4
.Lay er2 1 . I nd epend ent List C g end er # : 1 ." M eans !
1 # $
5 , 6. I nd epend ent List C " 3 Prev io u s 4 C 1 . C N " : " O K
4 3 ;
Report DEGREE GRO U P A
B
C
T o ta l
117
GENDER F e m a le M a le T o ta l F e m a le M a le T o ta l F e m a le M a le T o ta l F e m a le M a le T o ta l
M e a n 75.33 92.67 8 4.0 0 79.0 0 8 7.25 8 5.60 59.33 66.0 0 62.0 0 69.0 0 8 4.33 77.63
N
3 3 6 1 4 5 3 2 5 7 9 16
S t d . De v i a t i o n 6.8 1 6.43 11.19 . 8 .77 8 .44 4.51 2.8 3 5.0 5 10 .28 12.43 13.65
.1
.2
.3
( Test o f Linearity . E 1 ) : 4 #
% ) . + ) Linear trend . 3 F H $ 0 1 -
% 1 " %= ) " . E 1 A .O ne-W ay ANO V A : " M eans !
!
Test fo r Linearity
) 1 # "
; 1 (1S9) 1 1 # 9
ANO V A and
eta $ E 1
: " 5 , 6 7 <0
M eans : O ptio ns ANOVA Table
P R O D U C T * M E T H O B De tw e e n G ro u p s W ith in G r o u p s T o ta l
( C o m b in e d ) L in e a r ity D e v ia tio n fr o m
S u m o f S q u a re s 402.000 86 .400 L i n e a r 315 i t y .6 00 15 2.000 5 5 4.000
d f
3 1 2 8 11
M e a n S q u a re 134.000 86 .400 15 7 .800 19 .000
F 7 .05 3 4.5 47 8.305
Measures of Association P RO D U C T * M E T H O D
R -.395
RS q u a re d .1 56
E ta
.8 52
E ta S q u a re d .7 2 6
. (F=7.05 3 ) % ) %. 1 ) C $ 1 # " #
: " . 3 % - %) 1 N # ! SS D ev iatio n Fro m Linearity = SS. (Co mbined ) – SS. Linearity =402-8 6 .4=3 15 .6 : " Test fo r Linearity
1 - F 2 ;
F=M S. D ev iatio n Fro m Linearity / with in G ro u ps M S.=15 7.8 /19=8 .3 1
118
S ig . .012 .06 6 .011
% ) . E 1 " ) @ (
C A 3 0. 011 + " 1 P-v al u e 2
. 3 H . + %5 - M 1 1 - / . C " 3 ? . ( P-V al u e H ) # 2S8 1 6 )
) 1 M easu re o f asso ciatio n (.1 -) 2 = > E ta 2 $ 1 .1 - ) C $ 0 7 1 C 0 M @
? #
0 (pro d u ct) ) " % 1 1 # E ta-Sq u are J .1 C E ta-Sq u are = SS. between G ro u ps / SS. To tal = 7 (M eth o d ) # 402/5 5 4= 0.726 . (pro d u ct) 1 Simpl e Co rrel atio n .1 .1 - # ) # R 2
# 4C 1 % 1 D 3 1 ) 1 3 1 (M eth o d )
B 9 > , R-Sq u are M u l tipl e R ) .1 - # ) # R E
. Linear Reg ressio n C . -
O ne S am p l e T-Test
T ( 2 – 8 )
? . Sig nificant D ifference + ) H = H $ 1 - 0 ? . 9 A C @ A .
Co nstant 1 2 3 ) D %1 +
. (n< 3 0) 9 ! % ) " 1 - # ) Co nfid ence I nterv al
# A 2 < 52 ) 1 B 4 10 , 3 # W eig h t
#
. D ata ed ito r $ $
W E I G HT 1.10 1.10 .90 .8 0
.8 0
1.20
1.20
1.00
.90
1.20 " ;" .
@ 0 @ 1. 25 ) D %1 + ? " 1 . E 1 " ) @ 1 .1 . %1 %5 - M 1 1. 25 + - ? . E 1 " " 1
. ? " 1 . " %99 9 .2
S: " H1 " 1 H0 ) @ 1
#
H 0 : µ = 1.25 or µ - 1.25 = 0 H 1 : µ ≠ 1.25
t=
S: " 1 - t ! A x−µ
s/ n n=10 ) " + ) H - # S =.16 2 ) " 1 .
# =1.020 x 7
? 1 ! & F 1. 25 + ) @ ; 1 ? " 1 .
µ )
119
. (5 1 # 1 2 S x ! A ; ) v = n-1 = 9 1 t ? 4
: % . ? 1 1 - 0
. $ Anal y z e Co mpare M eans O ne sampl e T-Test : " D 1 1 + O ne sampl e t-Test ! , 6
: # $ D 1
+ O ptio ns !
, 6 O ptio ns 4
1 1 7 ( # ; " . ) 9 O ptio ns . 1
.Co nfid ence I nterv al # %99 9 0
T-Test / ) 9 0 ? # ) D 0 M issing V al u es #
@ O ne sampl e T-Test !
Test V ariabl es + % 3
: $ E F (
" M issing Cases 9 0 %- ) 1 : E x cl u d e Cases Anal y sis by Anal y sis
9 0 2 + - 9 0 2 C " 3 D T 1 D " 3 M +
% " < 0" ) D + T ! A ;- 2 E
. # " @
% . (9 0 G )V al id ! %- @ : E x cl u d e Cases List W ise
% ) % 1 6 2 ) 1 D E % 9 0 = 6 % P . # " @ % " < ) F ( % F , 9 0 G
- 9 0 2 ) # " " , 5 C " 3 + ' - #
. < C " 3 Test V ariabl es / -
: # " " 5 , 6 O ne sampl e T-Test !
12 0
O K
4 3
T-Te s t One-Sample Statistics
W E IG H T
N
10
M e a n 1. 02 0
S td . D e v ia tio n . 16 2
S td . E rro r M e a n 5 . 12 1E - 02
One-Sample Test T e s t V a l u e = 1 .25
W E IG H T
t -4.492
d f
9
S i g . ( 2-ta i l e d ) .0 0 1 5
M e a n D iffe r e n c e -.23 0
99% C o n f i d e n c e I n te r v a l o f th e D iffe r e n c e L o w e r U p p e r -.3 96 -6 .3 6 E -0 2
F t = ( 1.020-1.25 )/ 0.05 12 = -4.492 ! ; 1 t ! A ; 7 M v = 9 1 )
t(tab t 1 , + t(cal .) 1 t 1 H )
B ) t 2 7 t (cal.) ≥ t (tab.), v, α / 2
H0 (
7 α -
: ( Two Tail ed test . 1 -) α / 2 - M (t ? 4 # t, 9, 0.025 = 2.26 2 ( α = 5% ) t, 9, 0.005 = 3 .25 0 ( α = 1% ) E ) @ ( J 1 (4.492) 1 t " . 1
. %1 %5 - 1. 25 3 < ) H " ? " 1 .
+ " 1 @ 0
C . C " 3 4 P-v al u e
C " 3 ) 1 - .
Sig . SPSS 5 1 # 1 2 9 $ 1 , 1 %) 4 # - B - ,
7 . ) @ 3 (
α 2 # 2 , E 1 P-v al u e H ) . F = 3 #
. P-v al u e ; . L @ .. . α # 2 P-v al u e % ) @ (
T-d i s t r i b u t i o n
0.0007 5
0.0007 5 -4 . 4 9 2 4 .4 9 2
12 1
0
P-v al u e = Pr ( t ≥ 4.492 ) + Pr ( t ≤ −4.492 ) =0.0007 5 + 0.0007 5 =0.0015 Pr o babi l i ty # - # Pr %1 %5 - ) @ (
P-v al u e <0.01 P-v al u e < 0.05
1
M e an Di f f e r e n c e ? . ) . 1 0 " %9 9 9 0 1 1 : " , 1
Pr ( − 0.396 < x − µ − 0.23 < −0.0636 ) = 9 9 %
K <- 1 ! & # " # ) - # " 2 . 1 0 " 9
: " µ ? . %9 9 9 1
Pr ( x - t9 , 0.005 * (S/ n )< µ < x + t9 , 0.005 * (S/ Pr ( 0.8 5 3 6 < µ < 1.18 6 4 ) = 9 9 % (
n) )=9 9 %
D " 3 %9 9 + 1.1864 0.8536 1 ? . ? # +
1 - . 1 ) F 9 B ? 1.25 %5 - M 1 ) @
. % @ 0
I n d e p e n d e n t s a m p l e s T-Te s t T ( 3 8 )
/ T ! A # ) % - 3 . 1 " 1 - # ) H
. 1 -
!
# < 1 12 1 B A . 0 ! B
9.4 8 .4 1 1 .6 7 .2 9.7 7 .0 1 0 .4 8 .2 6 .9 1 2 .7 7 .3 9.2
- 0 ! 1 1
1
: 5 % , 1 1 A 12.5
H 1 : µA ≠ µ B
% 2
9.4 1 1 .7 1 1 .3 9.9 8 .7 9.6 1 1 .5 1 0 .3 1 0 .6 9.6 9.7
. 1 + ) 1 ; " .
H 0 : µA = µB
122
1 1
#
: @ 0 1 + . %1 %5
Pr o te n
: % . ? 1 K 0
7 # $ , 6 Data E d i to r . 4 G r o u p
Proten G rou p 12.50 9 .4 0 11.7 0 11.3 0 9 .9 0 8 .7 0 9 .6 0 11.50 10.3 0 10.6 0 9 .6 0 9 .7 0 9 .4 0 8 .4 0 11.6 0 7 .20 9 .7 0 7 .00 10.4 0 8 .20 6 .9 0 12.7 0 7 .3 0 9 .20
A A A A A A A A A A A A B B B B B B B B B B B B
% 1 # P 1
1 1
#
. $ An al y z e C o m p ar e M e an s I n d e p e n d e n t Sam p l e s T Te s t + I n d e p e n d e n t Sam p l e s T Te s t ! , 6
: " D 1
Te s t V ar i abl e s 2 Pr o te n
# P 1 2
G r o u p i n g V ar i abl e 2 ( 4 ) G r o u p
7 De f i n e G r o u p s 4 . 3 B A ? H )
C ) B A 4 2 D G r o u p
D < " 3 2 1 E ( d i c h o to m o u s V ar i abl e !
. 4 % - 9 ! 9 1 H 1 4 ;
C u t Po i n t # ! . # = ? M . K
4 10 # 2 2 , % - # ( 10 <= ) De f i n e G r o u p s
E F ) 3 10 + 1 2 , % - 9 3
. (N u m e r i c < 3 ; 4
0 6
> 0 D " I n d e p e n d e n t s am p l e T Te s t ! . 1 0 1 1 + Te s t V ar i abl e s
O p ti o n s 4
. O n e Sam p l e T Te s t !
2 # A : 6 = . < ) % 9 ) 3
: 5 , 6 I n d e p e n d e n t s am p l e T Te s t !
O K
Group Statistics
P R O T E N
123
G R O U P A B
N
12 12
M e a n 10 . 4 0 0 0 9 .0 0 0 0
S td . D e v ia tio n 1. 13 14 1. 8 7 4 2
S td . E M e a .3 .5
rro r n 26 6 4 10
4 3
Independent Samples Test L e v e n e 's T e s t f o r E q u a l i ty o f V a r ia n c e s
P R O T E N
E q u a l v a r ia n c e s a s s u m e d
F
2.776
t- te s t f o r E q u a l i ty o f M e a n s
S ig .
.1 1 0
t
d f
2.21 5
1 8 .0 8
2.21 5
E q u a l v a r ia n c e s n o ta s s u m e d
.0 3 7
1 .4 0 0
S td . E rro r D iffe r e n c e .63 20
8 .9 3 6E - 0 2
2.71 0 6
.0 4 0
1 .4 0 0
.63 20
7.267E - 0 2
2.7273
S ig . ( 2- ta i l e d )
22
9 5 % C o n fid e n c e I n te r v a l o f th e D iffe r e n c e L o w e r U p p e r
M e a n D iffe r e n c e
) , 9 E ) 1 + ( 0 C M 1 - 6 = 2 % 1 + 3 ( 0 σ 2 = σ 2 + E C 0 . σ 2A ≠ σ B B A + %5 - M 1 ) @ ( C ) P-V al u e = 0.03 7 <0.05 2 E %1 - M 1 1 - . 0 ! 1 1
. 1 )
. %1 - M 1 ) @ # 1 , P-V al u e > 0.01
) @ # 1 2 C 3 P-v al u e = 0.11>0.05
E 1 >
L e v e n 1
. ) , 9 E ) 1 (+ ) >
2
1 "
P a i r e d -S a m p l e s T-Te s t T ( 4 8 )
7 9 ( 3 ) 3 . 1 0 ) H $ - 1 - # )
. ) # 1 2 # 1
. 1 0 ) 1 <= B 4 C " 3 ) % $ . < ! $ 12 3 F ) 1 ) 3
% 3 4 . # ) . 2 % . $ 3 / 0 ! 9 (B A) 0 ! : ) . 2 # # ! # % 1 B H
A B
! 1 M % 3 4 A H
N 4
! 1 A
1
2
3
4
5
6
7
8
9
10
127 135
195 200
162 160
170 182
143 147
205 200
168 172
175 186
197 194
136 141
. %5 - M 1 ! " B & . + 1 " @ 0 1 ; " .
: % . ? 1 1 - 0
An al y z e C o m p ar e M e an s Pai r e d Sam p l e s T Te s t . $ : # $ C " 3 D 1 1 + Pai r e d Sam p l e s T Te s t !
124
:
, 6
> 0 = # A ; 7 b a 0 ! % $ = b a
: % . ; 4 % $ 1 3 1 Pai r e d v ar i abl e s 2 % 2
. F - > 4 1 a
. < ) - > 4 1 b ?
Sh i f t Q 0 . @ .2
2 C #
Pai r e d v ar i abl e s
.1
4 .3
: " 1 - 5 C " 3 # ! " O K
4
Paired Samples Statistics
P a ir 1
M e a n 167.80 171.70
A B
N
10 10
S td .D e v ia tio n 2 6.5 8 2 4 .60
S td .E rro r M e a n 8.4 0 7.78
Paired Samples Correlations P a ir 1
N
A & B
10
C o r r e la tio n .9 7 8
S ig . . 000
Paired Samples Test P a ir e d D iffe r e n c e s
P a ir 1
A-B
M e a n
-3.90
S td . D e v i a ti o n
5 .7 4
S td . E rro r M e a n
1 .8 2
9 5 % C o n fid e n c e I n te r v a l o f th e D iffe r e n c e L o w e r U p p e r -8 .01
.2 1
t
-2 .1 4 7
d f
9
S ig . ( 2 -ta i l e d )
. %1 %5 - M 1 + ) 0.9 7 8 1 . 1 - # ) ; 7
.06 0
+ H 0 : µA = µB ) @ # 1 2 C 3 P-v al u e =0.06 0>0.05 2 E T 1 - 1 1 . . 0 ! B & . 1 ) % = 3
125
Analysis of Variance
% 1 3 " % ) 1 N 1 ! @ % " ) 1 # " 1 !
. AN O V A Tabl e 1 # " # 1 H ) # # " 5 R
" 0 " F ! C
% ) 1 H ) % ) 3 % . + @ 1 # " / H ,
@ 0 1 - # ) + t 1 - < ) 1 ) , , 9 ) ( Tr e atm e n ts % = ) ) . . 3 . + 1 !
One Way ANOVA ( 1 9 ) % . # % = 1 \ ) N B - 3 !
: 1#
. ) 1 %
: # 1
.
5 0
3 4 8
2
1
47
55
61
64
64
55
52
52
49
55
45
41
44
50
1
2 3 4
J 1 ) J ; # " ! J , $ # , $ . : ! . 63R
J 19 89
: " ; " .
.%5 - M 3 ! . % . 1 0 ) 1 1 # " / : " ;" . F 1 1 3 ! . 1 0 ) , 6
+ ) 0 . 1 ( . ) ) # . 1 0 ) 1 . %5 - M L.S.D. !
. , @ 1 1 . . 1 4 3 2 . # . 1 0 ) 1 @
. Du n n e tt . 1 (9 . )
.1
.2 .
.;
. % . + 1 " ) @ 1 1 # " / H , .1
: @ 0 1 + # 2 C " 3 . . + 3 C " 3 R H 0 : µ1 = µ 2 = µ 3 = µ 4
" 1 @ 0
H 1 : µ1 ≠ µ 2 ≠ µ 3 ≠ µ 4
) . # F = 3 #
. . " ? . # µ 7
. . #
126
: % . ? 1 1 # " /
: # $ C " 3 Data E d i to r 2 % 1 # A m e th o d 1 1 1 2 2 2 3 3 3 4 4 4
p ro 5 4 4 5 6 6 5 4 5 5 4 4 5
7
d u c t 8 5
4
An al y z e 4 5
C o m p ar e M e an s
O n e -W ay N O V A
+ O n e -W ay AN O V A ! 9
: " D 1 1
2 0 4 1
, 6
: 7
< 1 ; # 1 # ) # : De p e n d e n t Li s t F Fac to r % ) > 0 (% ) ) - 1 D < " 3 . < 3 . De p e n d e n t @ % 3 1 1 # " # 3 C " 3 # !
# 3 ! . N # % 0 H ) # ) + # # : Fac to r
.N u m e r i c < 3 < ;
: 1 # " # 5 1 (
) O K
4 3
ANOVA PRODUCT
S u m S q u a 4 0 2 1 5 2 5 5 4
B e tw e e n G ro u p s W ith in G r o u p s To t a l
) @ (
127
? .
o re .0 .0 .0
f
s 0 0 0 0 0 0
d f
3 8 1 1
M e a n S q u a re 1 34 . 0 0 0 1 9 .0 0 0
F 7 .0 5 3
S ig . .0 1 2
, 0.05 # 2 F ! & 1 ! P-V al u e =0.012 2
. ? 1 3 ! . % . 1 ) + %5 - M
# 2 C " 3 . . + 3 ) , . % . 1 )
< 6 M u l ti p l e
9 ) % C E " % ) B 4 # 0 ) 1 -
Po s t H o c
!
: % . N 1 E 1 Du n n e tt L.S.D. . 1 C o m p ar i s o n s , 6 O n e -W ay AN O V A ! : " D 1
Po s t H o c 4
+ M u l ti p l e c o m p ar i s o n s
.2
9 I 1 1 Du n n e tt LSD $ E 1 2 7 9 ) % " 9 3 . 6 =
. Fi r s t 2 ( Fi r s t , Las t ) C o n tr o l C ate g o r y 9 . 3 ;
. H . ) 1 - N ? , 1 ;" . 9 . . C
. Si g n i f i c an c e Le v e l %5 ; " . ) M < . Te s t : % C " 3 # !
O K
4 C o n ti n u e
Multiple Comparisons
4 3
Dependent Variable: PRODUCT
( I ) M E TH OD 1
L S D
2 3 4 Du nnett t ( 2- s ided)
a
2 3 4
( J ) M E TH OD 2 3 4 1 3 4 1 2 4 1 2 3 1 1 1
*. Th e m ean dif f erenc e is s ig nif ic ant at th e . 0 5 lev el.
M ean Dif f erenc e (I-J ) - 11. 0 0 - 2. 0 0 5 .0 0 11. 0 0 9 .0 0 16 . 0 0 2. 0 0 -9 .0 0 7 .0 0 -5 .0 0 - 16 . 0 0 -7 .0 0 11. 0 0 2. 0 0 -5 .0 0
* * * * * * *
S td. E rro 3. 5 3. 5 3. 5 3. 5 3. 5 3. 5 3. 5 3. 5 3. 5 3. 5 3. 5 3. 5 3. 5 3. 5 3. 5
r 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6
a. Du nnett t- tes ts treat o ne g ro u p as a c o ntro l, and c o m pare all o th er g ro u ps ag ains t it.
128
S ig .
. 0 15 .5 9 0 . 19 8 . 0 15 . 0 35 .0 0 2 .5 9 0 . 0 35 .0 8 5 . 19 8 .0 0 2 .0 8 5 . 0 37 .8 9 6 . 40 9
9 5 % L o w er B o -
-
-
-
-
-
Co nf idenc e I nterv u nd Upper B 19 . 21 10 . 21 - 3. 21 2. 7 9 .7 9 7 .7 9 - 6 . 21 17 . 21 - 1. 21 13. 21 24. 21 15 . 21 .7 5 - 8 . 25 15 . 25
al o u nd - 2. 7 9 6 . 21 13. 21 19 . 21 17 . 21 24. 21 10 . 21 -.7 9 15 . 21 3. 21 -7 .7 9 1. 21 21. 25 12. 25 5 . 25
% . 1 %5 - M 1 ) % , 6 LSD . # ) 1 D 6 =
∗ =
3 ? 0.05 # 2 Si g . P-V al u e 2 % 7 (4 2)J(3 2)J (2 1) % ) . % . C " 3
C . . 1 %5 - M 1 ) C $ Du n n e tt 1 . 9 . 3 1 3 1 C . 1 3 .
: !
, 6 O n e W ay AN O V A !
: ! "
O p ti o n s 4 3
.… + ) H - J 1 .
# 0 !
> (
1 (# . ) % ) 1 > . 1 # " / , (
)1 (
: 7
) : De s c r i p ti v e
1 - : H o m o g e n e i ty -o f -V ar i an c e
0 1 >
1 ) 7 . Le v e n e ! A
. % ) . # . . (
) : M e an s p l o t
$ % " 9 0 < 2 + % - ) 1 : E x c l u d e C as e s An al y s i s by An al y s i s
. . # " 1
. % + 9 0 < 2 + % - ) 1 : E x c l u d e C as e s Li s tw i s e O n e -W ay
. 9 0 2 C " 3 % 1 / ) + $ E , - #
!
O K
4 F = 3 !
C o n ti n u e 4 3
: 5 (
3 AN O V A
Test of Homogeneity of Variances
>
PRODUCT L e v e n e S ta tis tic .6 6 7
d f1
3
3 ) " 1 @ 0 @
d f2
8
( 1 >
S ig . .5 9 6
) ) @ 1 1 F = 3 B
@ # 1 2 C 3 P-V al u e =0.5 9 6 >0.05 2 7 Le v e n e ! A 1 ( 1 . ( Le v e n e ! A # E x p l o r e ? ).% 1 >
M e a n s Pl o t s
129
1 " )
: ) # 1 .
# . .
70
Mean of PRODUCT
60
50
40
1
2
3
4
METHOD
Orthogonal Comparisons ( 11– 9 )
. G % ) (
) 1 1 / E 1 7 1 , ; 6 )
C o n tr as t 1 H ) " % t-1 D E t 3 ( % 3 ) % )
]Q = ∑ Ci Yi. w i th
: . 2 = ) E + (% = 1 )
∑ Ci = 0
C o e f f i c i e n ts % = ) Ci i ) N # Yi. 7 O r th o g o n al ( ) ) " , E Q2 = ∑ C 2i Yi. Q1 = ∑ C1i Yi. D + SSt% ) % ) 1 N D " 3 ∑ C1i C 2i = 0
A
# ) 1 & 1 9 , # " % t-1 C t-1
: # E 1 L @ . 9 C " 3 % F :2 #
) 1 E 1 4 3 % 1 % " ^ 0 C " 3 = ) N E 1 % Yi. 16 8 18 8 16 8 17 2 144
40 42 46 43 36
W e i g h t 42 47 44 45 37
40 48 42 42 36
# % 6 N # % 46 51 36 42 35
1 2 3 4 5
: . :
. 56
: " ;" .
. % ) % . 1 0 ) 1 - 1 # " / Q1 = 4Y1. − Y2. − Y3. − Y4. − Y5. = 0
13 0
: t-1 " ) 1 % ) 1
.1
.2
Q2 = Y2. + Y3. − Y4. − Y5. = 0 Q3 = Y2. − Y3. = 0
Q4 = Y4. − Y5. = 0
tr e at 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5 5
: " Data E d i to r 2 C % 1 # A 1
w e ig h t : 4 6 4 0 4 2 ! " # A n a l y z e C o m p a r e M e a n s O n e -W a y A N O V A 4 0 : % & ' O n e -W a y A N O V A $ 5 1 4 8 4 7 4 2 3 6 4 2 4 4 4 6 4 2 4 2 4 5 4 3 3 5 3 6 3 7 3 6
!
, 6 O n e -W ay AN O V A !
C o n tr as ts
4
# A C " 1 1 M " 9 % # P 1 7 C o n t r a s t s
: " , = )
4# ) @ A A d d 4 4 2 ; C o e f f i c i e n ts " ? 1
. # 0 # . C
•
- # ) @ A A d d 4 C o e f f i c i e n ts " ? 1 -1 2 ;
. # 0 # . C 1
•
- # ) @ A A d d 4 C o e f f i c i e n ts " ? 1 -1 2 ;
. # 0 # . C 1
•
- # ) @ A A d d 4 C o e f f i c i e n t s " ? 1 -1 2 ;
. # 0 # . C 1
•
- # ) @ A A d d 4 C o e f f i c i e n t s " ? 1 -1 2 ;
. # 0 # . C 1
•
131
N e x t 4 % = ) # & . C % = ) " 2 , 1
, 6 . % 1 . C % = ) # A . > 0 1 % = ) # P 1 1 : " C o n t r a s t s !
<= C % = )
.P r e v i o u s 4 1 C 9 ) " N e x t 4 C # =
5 1 O n e -W a y
A N O V A !
O K 4 C o n tin u e 4 : B (
)1
ANOVA WEIGHT
S u m S q u a 2 48 1 3 0 3 7 8
B e t w e e n Gr o u p s Wi t h i n Gr o u p s To t a l
o re .0 .0 .0
f
d f
s 0 0 0 0 0 0
4 1 5 1 9
M e a n S q u a re 6 2 .0 0 0 8 .6 6 7
F 7 .1 5 4
S ig . .0 0 2
. %1 %5 - M 1 ( = ) ) % ) % . 1 0 ) C $ F 1 Contrast Coefficients C o n tra s t 1 2 3 4
1
4 0 0 0
2
-1 1 1 0
T R E A T 3
-1 1 -1 0
4
-1 -1 0 1
5
-1 -1 0 -1
% ) t 1 1 # . ) 1 % % = ) 1 F = 3 #
1 P-V al u e =1 > 0.05 %5 - M 1 (Q1=0) ) G C L @ D
P-V al u e < 0.05 %5 - M 1 ( 0 ! 3 < H " ) ) , %
: " B V al u e o f C o n tr as t 2 " ) ? . % 1 + ( V al u e o f C o n tr as t = ∑ Ci Yi. / r . 4 :
132
: r
Contrast Tests V al u e of Contrast Contrast S td . E rror W E I G H T A ssu m e e q u al v ari anc e 1s .00 6 .5 8 2 1 0.00 2 .9 4 3 5 .00 2 .08 4 7 .00 2 .08 D oe s not assu m e e q u al1 .00 6 .3 9 v ari anc e s 2 1 0.00 2 .9 7 3 5 .00 2 .8 6 4 7 .00 .8 2
7 … 1) J
3 2 3 3 1 8
t .000 .3 9 7 .4 02 .3 6 3 .000 .3 6 5 .7 5 0 .5 7 3
d f
4 .7 6 .8 5 .8 4 .8
S i g . ( 2- tai l e d ) 1 .000 1 5 .004 1 5 .03 0 1 5 .004 2 7 1 .000 2 3 .01 2 8 0 .1 3 2 00 .000 1 5
Trend Analysis ( 219)
J . % 1 C % ) % ) 1 N 4
# " 0 % ) 3 # t 7 t-1 + Polynomial ) 0 " % <= # ) % 3 9 1 3 , % ) ;
0! 1 3 9 (
0" % 1 ) 1 H , )
. > # ) # M 1 ) M
D + 5-1=4 + ) E 1 # " % ) % ) 1 N # "
7 . ) 1 J 1) J J . 1 C "3 # ! & 1 : " Contrasts !
6 - . Contrasts % % 0 !
1
> 0 , , @ ) 1 3 " % 1 F < " 3
) Polynomial ) 1 Coef f icients % = ) 1 C B C "3 # !
133
O ne-w ay AN O VA !
O K
4 Continu e 4 3 .4th
:
ANOVA WEIGHT B e tw e e n Gr o u p s
( C o m b in e d ) L i n e a r Te r m Q u a d r a tic Te r m
Wi t h i n Gr o u p s To t a l
S u m o S q u a re 248 . 0 0 10 2. 40
C o n tra s t D e v ia tio n
C o n D e v C u b i c Te r m C o n D e v 4t h - o r d e r Te r m C o n
tr ia tr ia tr
a s tio a s tio a s
t
t
t
n n
f 0
4 1
M e a n S q u a re 6 2. 0 0 0 10 2. 40 0
145 . 6 0 0
3
9 2. 5 7 1 5 3. 0 29 1. 6 0 0 5 1. 429 5 1. 429 130 . 0 0 0 37 8 . 0 0 0
1 2 1 1 1
0
s
d f
15 19
F 7 . 15 4 11. 8 15
S ig . .0 0 2 .0 0 4
48 . 5 33
5 .6 0 0
.0 0 9
9 2. 5 7 1 26 . 5 14 1. 6 0 0 5 1. 429 5 1. 429 8 .6 6 7
10 . 6 8 1 3. 0 5 9 . 18 5 5 . 9 34 5 . 9 34
.0 0 5 .0 7 7 .6 7 4 . 0 28 . 0 28
? ) 1 % 1 C " 3 Betw een Grou ps % ) 1 % ) 1 N ? 4 D 6 -
- M 1 1 3 ) % , 6 % 1 ? 1 # 9 / . 3
. Cu bic term 1 ) 1 3 % 5
Tw o W ay AN O V A (29)
C @ A # # ) % ) % . + 1 ) 1 # " 0
R CB
$ ) " % 3 . ! ; B # ) % . + 1
. ; ! Desig n : 3#
K 0 1 + # C "3 # ! $ 3 " % 3 . 2 1
(# # ) ) % . & N ) 1 % 2 ) ? . 2 ) 1 ( ) ) . : ! ( )
(
# ) 1) % 3 . ) % ) 1 %
D
C
B
A
0
-1 -1 -3 -4
1 1 0
4
-2 -2 -4
-5
1 0 0
( ) 1 2 3 4
" #
: . 83 #
1984
! "
N % . 1 0 ) 1 - ) 1 # " # 7 1 ; G
. % 5 - M 1 car% N 1 0 ) K Tyre % . & : " Data E ditor 2 % 1 # P 1 1
134
car A A A A B B B B C C C C D D D D
tyre 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
1 % @
th in 4 1 0 0 1 1 0 -5 -1 -1 -3 -4 0 -2 -2 -4
: $ * % : +
Analyze G ener al L i near M o d el U ni v ar i at e : % + & # ' U ni v ar i at e $ !
" # ,
2 # ) % ) 1 3 C " 3 Fixed Factors " ) "
% 1 # ) 6 - . R andom Factors # ) E # ) % ) 3
; 7 O ne-W ay AN O VA D > ) C " 3 < 4 < Fixed Factor
K Fu ll Factorial <- 1 Cu stom J M odel ! ) (car*tyre) 1 # " #
: " D 1 ) 1 M odel !
. < 3 < Factor , 6 M odel 4
I nteraction # 3 0 , 6 ; G
-
, 6 7 1 E. " %
. B % 1 @ C " 3 # ) I nclu de I ntercept in M odel $ E 7
. B F 13 1 )
# " # , 6 A E f f ects % E N ) # ) Bu ild Terms 1 M odel C Factors &
135
Cov ariates car tyre # 1 2 7 1
E ) 1 ) M ain E f f ects % E , 6
.( M ain ef f ects @ Bu ild Terms
: B C "3 # !
Between-Subjects Factors T Y R E
CAR
A B C D 1 2 3 4
4 4 1 , #
N
U niv ariate !
O K
Continu e 4 3
4 4 4 4 4 4 4 4 Tests of Between-Subjects Effects
Dependent Variable: THIN S o u rc e C o rrec ted M o del Interc ept TY R E C A R E rro r To tal C o rrec ted To tal
Ty pe III S u m o f S q u ares 69. 37 5 a 14 . 0 63 30 . 68 8 38 . 68 8 11. 5 63 95 . 0 0 0 8 0 . 938
df
6 1 3 3 9 16 15
M ean S q u are 11. 5 63 14 . 0 63 10 . 2 2 9 12 . 8 96 1. 2 8 5
F 9. 0 0 0 10 . 94 6 7 . 962 10 . 0 38
a. R S q u ared = . 8 5 7 ( A dj u s ted R S q u ared = . 7 62 )
S S . Corrected M odel = S S . TYR E + S S . CAR S S . Corrected Total = S S . Total –S S . I ntercept # . 1 B + GL M ) . B R
S ig .
.0 0 .0 0 .0 0 .0 0
2
9 7
3
: 6 #
: " Tw o-W ay AN O VA ) 1 1 # " # ( # # ! ? ) Tests of Between-Subjects Effects
Dependent Variable: THIN S o u rc e TY R E C A R E rro r C o rrec ted To tal
Ty pe III S u m o f S q u ares 30 . 6 8 8 38 . 6 8 8 1 1 .5 6 3 8 0 . 938
. % 5 . /
df
M ean S q 1 0 1 2 1
u are .2 2 9 . 8 96 .2 8 5
F 7 . 96 2 1 0 . 0 38
S ig . .0 0 7 .0 0 3
car # % , - tyer # $ % & # ' ( ) * +
0 ) # , F 2 C "3 # !
136
3 3 9 1 5
D < " 3 ) car tyre
:
1 # 3 0 , 6 &
: % . ? 1 ( %
.1
!
I nteraction Bu ild Terms # 0
tyre 1 ) % 2 > 0 Factors &
D ,
•
Cov ariates car tyre
•
.M odel
. (car ? S h if t Q 0 . @
. M odel C #
. M odel !
4
•
) . B # )
.2
Fu ll Factorial 1 4 1 / $ > 0 < " 3
. ) 1 # " / GL M
( 1 9 # 9 $ # ? ) 1 # " ) : 4 #
S h elf L ocation H ? 2 ; " " 3 1 % ) 1 # #
# $ % 2 ( # ) ) S tore S iz e ( # # ) ) S h elf L ocation H ? 2
D 48 53 60 57 7 1 7 5 # 3 % ) % . 1
C 65 7 1 7 3 8 0 8 2 8 9
0 )
B 56 63 69 7 8 7 5 8 2 1 ? )
S iz e
:
A_ 45 S mall 50 57 M ediu m 65 7 0 L arg e 7 8
1 # " # ; ".
- M 1 S iz e*L ocation # 3 0 ) 1 L ocation ? 2 % ) 1 S iz e
. < 1 K L @ ? % 5
location A S A S A M A M A L A L B S B S B M B M B L B L C S C S C M C M C L C L D S D S D M D M D L D L
137
size m all m all ed iu m ed iu m ar g e ar g e m all m all ed iu m ed iu m ar g e ar g e m all m all ed iu m ed iu m ar g e ar g e m all m all ed iu m ed iu m ar g e ar g e
sales 4 5 5 0 5 7 6 5 7 0 7 8 5 6 6 3 6 9 7 8 7 5 8 2 6 5 7 1 7 3 8 0 8 2 8 9 4 8 5 3 6 0 5 7 7 1 7 5
: " Data E ditor % 1 # P 1 1
: - . $ -
Analyze
: +
G ener al L i near M o d el U ni v ar i at e
: % + & # ' U ni v ar i at e $ !
" # ,
I nteraction # 3 0 C " 3 # ! ; G
Fu ll Factorial M odel 4
. $ ) E. " % 3
< " 3 ( 1 " . % E Cu stom % E / 4 ; G % A )
. Def au lt @ - Fu ll Factorial
# = D " 1 C " 3 siz e % D # . . 3 Plots 4
Prof ile Plots
!
, 6 L ocation " ? 1 % .
6 B ) " % . D 0 + I nteraction Plot : "
: " F = 3 ! % # A
.H oriz ontal Axis C Factors siz e # Plot
. S eparate L ines C L ocation #
•
C siz e*location # 3 0 H @ F <- ) L 1 ! Add 4 6 =
•
.# 0
. 7 # 3 % M # 3 . . # 3 , 0 S eparate Plots 2 . U niv ariate !
C N " Continu e 4
# 3 0 " E stimated M arg inal M eans % . (
: # $ 1 O ptions !
138
•
) O ptions 4
6 7 location*siz e
. 5 C "3 # !
U niv ariate !
O K
Continu e 4 3
Tests of Between-Subjects Effects
Dependent Variable: SALES So u rc e C o rrec ted M o del I nterc ept LO C AT I O N SI Z E LO C AT I O N * SI Z E Erro r T o tal C o rrec ted T o tal
T y pe I I I Su m o f Sq u ares 30 19 . 333a 10 8 27 2. 667 110 2. 333 18 28 . 0 8 3 8 8 . 9 17 25 8 . 0 0 0 1115 5 0 . 0 0 0 327 7 . 333
df
M ean Sq u are 27 4 . 4 8 5 10 8 27 2. 667 367 . 4 4 4 9 14 . 0 4 2 14 . 8 19 21. 5 0 0
11 1 3 2 6 12 24 23
F 12. 7 67 5 0 35 . 9 38 17 . 0 9 0 4 2. 5 14 . 68 9
Sig . .0 0 0 .0 0 0 .0 0 0 .0 0 0 . 663
a. R Sq u ared = . 9 21 ( Adj u s ted R Sq u ared = . 8 4 9 )
B ? < = D . 1 & 1 ) . B " - 5 # # Tests of Between-Subjects Effects
: " 1 # "
Dependent Variable: SALES So u rc e LO C AT I O N SI Z E LO C AT I O N * SI Z E Erro r C o rrec ted T o tal
T y pe I I I Su m o f Sq u ares 1 1 0 2. 333 1 8 28 . 0 8 3 8 8 .9 1 7 25 8 . 0 0 0 327 7 . 333
df
M ean Sq 367 9 1 4 1 4 21
3 2 6 1 2 23
u are .4 4 4 .0 4 2 .8 1 9 .5 0 0
% ) 1 K L ocation # ) % ) 1 ) % 2
F 1 7 .0 9 0 4 2. 5 1 4 . 68 9
Sig . .0 0 0 .0 0 0 . 663
C A $ F 1
. p-Valu e = 0. 663> 0. 05 % 5 - M 1 # 3 0 ) , 6 1 siz e # )
Esti m a te d M a r g i n a l M e a n s
LOCATION * SIZE
Dependent Variable: SALES LO CAT I O N A B C D
139
SI Z E Larg e M ediu m Sm all Larg e M ediu m Sm all Larg e M ediu m Sm all Larg e M ediu m Sm all
M ean 7 4 .0 0 6 1 .0 0 4 7 .5 0 7 8 .5 0 7 3 .5 0 5 9 .5 0 8 5 .5 0 7 6 .5 0 6 8 .0 0 7 3 .0 0 5 8 .5 0 5 0 .5 0 0
0
0
0
0
0
0
0
0
0
0
0
Std. Erro 3 .2 7 3 .2 7 3 .2 7 3 .2 7 3 .2 7 3 .2 7 3 .2 7 3 .2 7 3 .2 7 3 .2 7 3 .2 7 3 .2 7 9
9
9
9
9
9
9
9
9
9
9
9
r
9 5 % Co Lo w er Bo u 6 6 .8 5 3 .8 4 0 .3 7 1 .3 6 6 .3 5 2 .3 7 8 .3 6 9 .3 6 0 .8 6 5 .8 5 1 .3 4 3 .3
nf idenc e I nterv nd U pper Bo 5 6 8 1 5 6 6 8 5 6 5 4 5 6 8 5 5 6 8 0 5 6 6 6 5 6 9 2 5 6 8 3 5 6 7 5 5 6 8 0 5 6 6 5 5 6 5 7
al u nd .1 4 4 .1 4 4 .6 4 4 .6 4 4 .6 4 4 .6 4 4 .6 4 4 .6 4 4 .1 4 4 .1 4 4 .6 4 4 .6 4 4
. . 6 = 7 S iz e L ocation " ) 1 # 3 0 1 . .
4 . . 1 - ? 2 0 C $ < 1 4
. F 1 1 . 1 D " ! 3 location siz e " ) 1 # 3 0 3 $ '
P r o f i l e P l o ts
90
Estimated Marginal Means of SALES
Estimated Marginal Means
80
70
LOCATION 60
A B
50
C
40
Large
Medium
Small
D
SIZE
Covariance Analysis ( 3– 9)
( 1 ! ) " # 3 K ; ! 1 # " D # $ , 4 , "3 % ) E > 2 9 6 C "3 ' X
4 1 , 4 Cov ariates
(% ) ) G 3 E > 2 3 <= Dependent Variable ) Y 4 1 1 / " D 1 M C "3 ' 1 1 X 4 E Y 4 9 4 C "3
) " , 4 1 % = - % A ) ? . -
R
" (
1 , 7 1 E
. 1 1 4 3 / 3 ( 1 ,
. - 1 # " 1 ? ; " K $ 1 # "
X ; ! : 5 #
4 9 4 C " 3 0 " (% ) ) = 3 ) 1 E ^ C " 3 1 % , Y ^ 4 9 4 1 # . ) # % $
% ^
. 1 1 3 X ^ 4 1 1
140
O bserv ations 2 9 1 5 1
33 1 6 7
2 1 1 5 6
2 0 1 30
2 5 1 7 0
2 0 1 8 0
2 6 1 6 1
2 0 1 7 1
29 172 36 1 8 9
30 160 2 8 1 4 2
35 190 35 1 9 3
35 138 30 2 00
X 1 1 4 4 A ) 1 %
# 1
X Y X 31 2 4 1 6 9 1 8 0 Y 32 X 34 1 5 6 189 Y X 32 4 1 1 7 3 2 01 Y
) % . 1 0 ) 1 ; 2 7 1 7 0
30 1 6 5
141
X 30 27 20 21 33 29 24 31 20 26 20 25 34 32 35 35 30 29 41 32 30 35 28 36
Y 165 170 130 156 167 151 180 169 171 161 180 170 156 189 138 190 160 172 201 173 200 193 142 189
treat T1 T2 T3 T4 ".
. (K $ 1 # " ; " )
: # $ 1 Data E ditor 2 # % 1 ; treat T1 T1 T1 T1 T1 T1 T2 T2 T2 T2 T2 T2 T3 T3 T3 T3 T3 T3 T4 T4 T4 T4 T4 T4
(
1
: / + $ - .
Analyze G ener al L i near M o d el U ni v ar i at e : % & ' U ni v ar i at e $ !
: * 2 1 ! $ O K
0 1
" # ,
Tests of Between-Subjects Effects Dependent Variable: Y
T y pe I I I S u m o f S q u ares 2 8 45 . 9 6 9 38 . 6 6 8 2 .8 16 0 9 . 5 5 2 5 5 .0 6 9 9 32 3. 0 8 10 0 . 9
S o u rc e C o rrec ted M o del I nterc ept X T R E A T E rro r T o tal C o rrec ted T o tal
5 6
a
df
0 2 31 9 5 0 2 0 0 5 8
4 1 1 3 19 2 4 2 3
a. R S q u ared = . 35 1 ( A dj u s ted R S q u ared = . 2 15 )
M ean S q u are 7 11. 48 9 6 9 38 . 6 0 2 6 8 2 . 8 31 5 36 . 5 32 2 7 6 .5 7 9
: " K $ 1 # " 9 !
F 2 .5 7 2 2 5 .0 8 7 2 . 46 9 1. 9 40
S ig .
.0 7 1 .0 0 0 . 133 . 15 7
F = 3 # . 1 2
Tests of Between-Subjects Effects
Dependent Variable: Y S o u rc e T R E A T E rro r T o tal+ E rro r
T y pe I I I S u m o f S q u ares
a
1 6 0 9 .5 9 5 5 2 5 5 .0 0 2 6 8 6 4 .5 9 7
df
M ean S q u are
1 9 2 2
3
5 36 . 5 32 2 7 6 .5 7 9
F 1 .9 4 0
S ig . .1 5 7
a. R S q u ared = . 35 1 ( A dj u s ted R S q u ared = . 2 1 5 )
% 5 - M 1 ) @ # 1 2 C 3 P-Valu e= 0 . 157 > 0. 05 2 6 = . X ; ! 4 A ) 1 = ) ) 1 N % . + C "3 R
142
Correlation & Regression Analysis Correlat ion ( 1 10 )
, 1 K = , - # 1 2 = ) <= Correlation . 1 - 1 6 1 2 = ) C
) " ) N 0 ( . 2 = 3 ) % ? " D = , 9 4 C + ' 0 # 9 4 . G L inear < . 2 . 1 - < " 3 ( 3 2 = 3 ) , " 3 ; " . C + '
Correlation . 1 - # ) 1 H ) . 1 - > + > . N on L inear . (−1 ≤ r ≤ 1) 1 C 1– 1 D 2 Q r D 4 Coef f icients
?
S im p le L inear Correlat ion ( 2 10 )
. % 1 . 2= 3 (
1 . 1 . . 1 - # ) ;
1 2 = 3 3 ) - # ) , ( 0 ! 1 2 ) 9 !
2 C "3 # ! ")
. ( . G . 1 ) 2= 3
% @ 1 L ang " 1 ; = . 10 , % # % 1 L ang
6 0 6 8 6 0 7 4 8 0 8 4 8 0 7 2 6 2 8 2
M ath
5 6
: " S PS S 5 1 Data E ditor 2 , 6 M ath
6 0 6 4 8 2 7 6 7 2 7 4 6 6 6 4 8 6
: " ; ".
. S pearman ; . 1 # ) J Pearson . 1 . . 1 - # )
. % 5 - M 1 . 1 - # ) ) 1
!
143
:1 #
: % . ? 1 F = 3 ; . 0
, 6 Analyz e Correlate Biv ariate : " D 1
. $
.1
.2
+ Biv ariate Correlation
: % Correlation Coef f icients # @
. % " . 1 . . 1 - # ) B - : Pearson
R anks ; # ) 1 " ) = . 1 . 1 - # ) B - :K endall’s Tau
# ) + @ D . 1 9 ! 1 . 1 - # ) 1G
4 3 ! < 1 , . 3 A ( % % ) G = 6 M A . " ! <- 1 6 " 9 6 ; # A F
. K endall # ) 1 1 # ; " . 1 # ) : S pearman . S pearman Pearson $ 2
1 - . . @ 0 1 - Tw o Tailed $ Test sig nif icance #
. O ne Tailed $ ' H . @ 0
. ( S tar = 3 , 6 A ) ) % . 1 - " ) : Flag S ig nif icance Correlation : 5 , 6 O K
Correlations L A NG M A T H
P e a rs o n S ig .( 2 - ta N P e a rs o n S ig .( 2 - ta N
C o r r e la tio n ile d ) C o r r e la tio n ile d )
L A NG 1.000 . 10 .7 7 6 * * .008 10
* * . C o r r e l a t i o n i s s i g n i f i c a n t a t t h e 0.01 l e v e l ( 2 - ta ile d ) .
4 3
M A T H .7 7 6 * * .008 10 1.000 . 10
@ 0 1 - r = 0. 776 M ATH L AN G 1 1 . . 1 - # ) 2
H 0: ρ = 0
H1 : ρ ≠ 0
144
: ( . 1 )
3 k ? # n 7 n-k 1 T ? 4 ? 1 T ! A T =r P- C " 3
n−k
1− r2
= 0.776
10 − 2
1 − 0.776 2
# ! K
" T ? 4 ) # ) Transf orm
. %
= 3.48
Compu te # = Valu e
1 . 1 - C $ P-Valu e=0. 008<0. 05 1 2 . (1 − CDF .T (3.48,8)) * 2 = 0.008
+ ) H = - ) % 5 - M 1 0 ! 3 < ) H " % @ "
. (< @ % 1 - M 1
: 1 ; . 1 # ) # B
Nonparametric Correlations Correlations S p e a r m a n 's r h o
L A NG M A T H
C o S ig N C o S ig N
r r e la tio n C o e ffic ie n t .( 2 - ta ile d ) r r e la tio n C o e ffic ie n t .( 2 - ta ile d )
* * . C o r r e l a t i o n i s s i g n i f i c a n t a t t h e .01 l e v e l ( 2 - t a i l e d ) .
L A NG 1.000 . 10 .7 8 6 * * .007 10
M A T H .7 8 6 * * .007 10 1.000 . 10
S pearman # ) H1 : ρ ≠ 0 " 1 @ 0 @ H 0 : ρ = 0 ) @ 1 S pearman . 1 # ) P-Valu e 1 2 . F = 3 Pearson 1 T ! A > 0
. % 1 K % 5 - M 1 # ) ) C $
!
O ne Tailed $ '
:
H . . 1 - # ) @ 1 -
: 1 I Biv ariate Correlations
: @ 0 1 1 5 1 1 9 . 1 - # ) 2 % H 0: ρ = 0
H1 : ρ f 0
:
! " 0.766
145
.1
Correlations L A NG M A T H
P e a rs o n S i g . ( 1- t a N P e a rs o n S i g . ( 1- t a N
L A NG 1.000 . 10 .7 7 6 * * .004 10
C o r r e la tio n ile d ) C o r r e la tio n ile d )
* * . C o r r e l a t i o n i s s i g n i f i c a n t a t t h e 0.01 l e v e l ( 1- t a i l e d ) .
# ! 3. 48
+
M A T H .7 7 6 * * .004 10 1.000 . 10
. 1 - , 0
T ! A ; 7
? 4 ) # ) Transf orm Compu te # = P-Valu e C " 3 H . 1 - 2 ; @ - 6 -
(1 − CDF .T (3.48,8)) = 0.004 " T
% @ " 1 . 1 - C $ P-Valu e=0. 004<0. 05 1 2 .
. (< @ % 1 - M 1 + ) H = - ) % 5 - M 1 0 ! 1
: @ 0 1 1 5 1 1 9 . 1 - # ) 2 % H 0: ρ = 0
.2
H1 : ρ p 0
2 C "3 # !
Partial Correlation ( 3 10 )
2 <= . 7 % 1 1 1 2 = ) 9 2 4 . 1 - # ) >
1 ") 2= 3 - / " / @ 1 " ) 1 2= ) " . 1 . 1 - # ) 3
) M ) 1 ) I ) M 7 # ) 1 E =
# 2 2 C " 3 # ! / / @ 1 " ) 1 2 = ) > 2 3 (D 1 ) ) I > 2 3 % 3 + ) 1 D < " 3 . 4 . 1 - 1 H ) . 1 - # )
. 6 1 2= )
: " ; " . 13 ) ` " 1
( 3 – 4 S 10 ) 1 6 # 9 % 1 "
. X3 % 1 1 X2 Y 1 4 . 1 - # ) ;
. X4 X3 % 1 1 X2 Y 1 4 . 1 - # ) ;
:2 #
.1
.2
.% 5 - M 1 ( . ) . 1 - % = ) ) 1 .3 !
146
, 6 Analyz e
Correlate Partial
: # ; ". " " D 1
. $
+ Partial Correlation
:#
J , 4 . 1 - # ) ; % # A Variables
. F ) 1 + (% ) # A Controlling f or . C "3 # !
--- PAR TI AL
CO R R E L ATI O N
Controlling f or. .
CO E FFI CI E N TS
(
1 . 0 0 0 0 0 ) P = .
. 2 8 5 1 1 0 ) P = . 3 6 9
X 2
. 2 8 5 1 1 0 ) P = . 3 6 9
1 . 0 0 0 0 0 ) P = .
( C o e f f i c i e n t
/
(
(
"
i s
---
X 2
Y
.
X 3 Y
"
O k 4 3
(
( D . F . )
p r i n t e d
i f
a
/
2 -t a i l e d
S i g n i f i c a n c e )
c o e f f i c i e n t
c a n n o t
> 0 # ) ( . ) 4 . 1 - # ) ) 1 -
b e
c o m p u t e d
r yx 2.x3 = 0.285 7
F = 3 # , 6 + 2 # 10 2 6 - . . 1 . 1 - # ) 1 - T ! A
2 T df = n – k = 13-3 = 10 7 T 1 - 4 = % ) # T =r
147
n−k
1− r2
= (0.2851)
13 − 3
1 − 0.28512
: " % 1
= 0.941
0 ! 3 < ) H " > 0
ρ ? " ) E , P-Valu e=0. 369 >
: # $ C " 3 Partial Correlations !
CO R R E L ATI O N
Controlling f or. .
X 3
CO E FF I
1 . 0 0 0 0 ( 0 ) P = .
. 2 3 3 8 ( 9 ) P = . 4 8 9
X 2
. 2 3 3 8 9 ) P = . 4 8 9
1 . 0 0 0 0 0 ) P = .
( C o e f f i c i e n t
/
(
i s
p r i n t e d
148
: " 5 , 6
C I E N T S - -
(
( D . F . ) i f
a
/
2 -t a i l e d
c o e f f i c i e n t
S i g n i f i c a n c e ) c a n n o t
. % 5 - M 1 0 ! 3 < ) H " !
; 1 % .
X 2
Y
"
;
X 4 Y
.
. % 5 - M 1
( ; " . ) X 4 X 3 % 1 1 X 2 Y 1 4 . 1 - # )
--- PAR TI AL -
"
0. 05 2
b e
c o m p u t e d
r yx 2.x3 x 4 , 6 D
:
O ptions 4 1 Pearson . 1 . 1 - # ) B
. Z ero O rder Correlations $ E Partial Correlations
R eg res s ion A naly s is ( 4 10 )
1 Dependent Variable ) 1 2 = 3 3 1 ) - B
# C " 3 B M R eg ressors I ndependent Variables " % # M
S imple R eg ression model . 1 - B 1 H )
L inear M odel $ % & M u ltiple reg ression M odel ) - B , . N on L inear M odel . G
( 1 4 10)
Y = B0 + B1 X + e : ) ! E : 7
) : Y # : X
. I ntersection Parameter + ! ? - . ? . " ) % 1 : B0
∆Y S lop Parameter # " ) : B1 ∆X 7 residu al 1 1 H ) Yˆ Y 1 0 $ ) E . :e . e = Y − Yˆ B1 =
M ! % ) 1 . B1 B0 - ) < 1 G ) 1 .
% @ 0 ; . 1 . - B < " 3 (O L S ) L east S q u ares M eth od . X Y 1 . 2 = 3
E . 1 > + @
:
. 0! " + . 1 N 4 $ ) / .
@ ) σ 2 + % 1 1 , $ ) / .
D O L S . 1 ) < @ . B1 B0
. ( H omoscedasticity $ )
> . $ < ) 1 . N 4 / .
- % = ) 1 ") % @ 0 1 -
. $ ) / . 1 Au tocorrelation . 1 3
.1
.2
.3 .4
.5
yˆ # 1 S catter plots . . # = . 1 . B % @ 1
S tandardiz ed R esidu als ) / . e $ ) E . D " 1 ( x ) C " 3
. # $ L @ C " 3 es , 4
149
e o r es
e o r es
R es id u als
yˆ
(a
(b
e o r es
e o r es
yˆ
yˆ
(c
. ( $ ) E . 1 >
(d)
yˆ
. ( " $ 3 ) # " % @ (a ) . y 9 4 1 $ ) E . 1 9 4 (b )
3 " $ ) $ ) E. 1 R
2 9 4 (c )
. ( B <= M B # ) ; ) . 2 = ) = 3 (d) 2 R
$ 10 ) ( 1 4 " ) Y
O bs. 1 2 3 4 5 6 7 8 9 10
Y 112 128 130 138 158 162 140 175 125 142
X 35 40 38 44 67 64 59 69 25 50
: 3 #
. @ X ) # % 1
: " Data E ditor 2 % 1 # A
: " ; ".
. B ) ) 1 . 2 = ) < @ 0 Y/X ) B . B1 B0 - " ) # % 9 5 9 B
15 0
.1
.2
. ANOVA 1 # " # B
$ ) / . # " ? ( R2 # ) # ) 1 ) . B 9 1 . 1 1
. < 1 $ ) / . I ) 1 . ? 4 1
L i n ea r An a l yz e
.3
.4
.5
: #
: % . ? 1 F = 3 ; . 0 Reg res s i o n L i n ea r 5 : Reg res s i o n
: 7
. ) # :D ep en d en t
# " % 3 # A . ( " % ) : I n d ep en d en t
Next 4 1 C Bl o ck
# - " " 2 D Bl o ck @
# 3
? Z # D B X # . Prev i o u s
Z Bl o ck 1 X # A F = Y )
. Bl o ck 2
. ( E n ter 3 - . ) - . N : M eth o d
) 2 , % - ) 3 # " # ) : S el ecti o n
Va ri a b l e
(5 1 Ob s erv a t 2 , % - C " 3 - B ! 2 <= ) -
. Ru l e 4 . 1
. S ca tterp l o ts $ # $ . ) D 2 : Ca s e L eb el s
: " D 1
151
+ S ta ti s ti cs !
, 6 S ta ti s ti cs 4
5
: % $ E 2
. t % 1 - B ) : E s ti m a te
. - " ) # % 9 5 9 : Co n f i d en ce I n terv a l . ANOVA R2 (
1 - No rm a l Pro b a b i l i ty Pl o t $ Pl o ts !
) : M o d el Fi t
, 6 Pl o ts 4
5
, 6 S a v e 4
5
. (> ; " . ) ) $ ) / . I ) 1 . ? 4
: " D 1
152
+ S a v e !
S ta n d a rd i z ed
K yˆ + U n s ta n d a rd i z ed Pred i cted Va l u es
6 -
? 1 ; " . . $ " S ca tterp l o ts # ) es + Res i d u a l s X % ; C D a ta
E d i to r 2 C (5 1 $ 3 ) @ A D < " 3 J
H @ Pre_ 1 E 1 U n s ta n d a rd i z ed Pred i cted Va l u es
H @ 7 Ob s erv a t Y
. Zre_ 1 E 1 S ta n d a rd i z ed Res i d u a l s
Op ti o n s " # $ % & # ' ( ) .L i n ea r Reg res s i o n : , - . + $ L i n ea r Reg res s i o n OK " + 5 Coefficientsa
U n s ta n d a r d i z e d C o e f f i c i e n ts M o d e l 1
( C o n s ta n t) X
B 85.044 1.140
a . D e p e n d e n tV a r ia b le : Y
S td E rro 9 .9 7 .19
. r 0 5
S ta n r d iz C o e ie n
d a e d ffic ts
Be ta .9 00
9 5% t 8.53 0 5.846
S ig . .00002 7 .0003 8
C o n f i d e n c e I n te r v a l fo r B
L o w e r Bo u n d 6 2 .052 .6 9 0
U p p e r Bo u n d 108.03 6 1.589
: " B 1 F = 3 # # =
1.140 1 . @
yˆ = 85.044 + 1.140 x (9. 97) (0. 195) 9 4 C + ' 9 ) 9 4 C $ # ")
. " 1 " ) " + ) E . # > 2 # 2 . 1 4 " : B1 # " ) @ 0 1 - T 1 # ) H 0 : B1 = 0
) @
H1 : B1 ≠ 0
" 1 @ 0
H 0 : B0 = 0
) @
: B 0 (% 1 ) ? . " ) @ 0 1 - T 1 # ) H1 : B0 ≠ 0
" 1 @ 0
: " 1 - " ) " T ! & P-Va l u e 2 . % 5 - M 1 ) @ (
. % 1 - M 1 ) @ (
P-Va l u e < 0. 05 %
P-Va l u e < 0. 01 %
. ) @ # 1 > 3
" ) P-v a l u e 0 . 0 1 # 2 0 . 0 0 0 38 + # " ) P-v a l u e
= + ") # ) @ (
, 0 . 0 1 # 2 0 . 0 0 0 0 2 7 + % 1
. B ) > ) ) # " ) , 6 0 ! 3 < H " " )
153
B " # " ) , Beta 1 , $ S ta n d a rd i z ed Co ef f i ci en t " )
+ - " ! # 1 ) # # ( X − X ) / S ) # ) 1 . ) % x * yˆ * 7 yˆ * = β x * " B0 ? . " ) C " 3 B : " % 1 " % 9 5 9 1 Pr(62.052 ≤ B0 ≤ 108.036) = 95%
: " # " ) % 9 5 9 1 # - # 1 Pr 7
Pr(.690 ≤ B0 ≤ 1.589) = 95% > 0 1 - F ! A C " 3 # $ ANOVA 1 # " # 1 H ) #
6 - ) # " ) T 1 - < a 1 - B1 # " ) 1 ! @ 0 .F=T2 < " 3 ( 1 = P-Va l u e 2 ANOVAb M o d e l 1
R e g r e s s io n R e s id u a l T o ta l
S u m o f S q u a re s 2661.050 622.950 3 284 .000
a . P r e d ic to r s : ( C o n s ta n t) , X b . D e p e n d e n t V a r ia b le : Y
d f
1 8 9
M e a n S q u a re 2661.050 7 7 .869
F 3 4 .17 4
S ig . .0003 8a
Co ef f i ci en t Of # ) - B $ ' @ #
1 # " # ; . B 9 < 1 ) R2 D 4 D eterm i n a ti o n R2 =
ExplainedVariations SSR 2661.05 = = = 0.81 Total Variations SST 3284
: "
0 ≤ R2 ≤ 1
+ . 2= ) 0 ( Y 2 " % - ) % 1 % 8 1 K 0
@ , % K E $ 3 # 3 C ? % 1 % 19 - B
. B 9 C " 3 K # % 10 0 R2 2 % 1 2 " ) C " 3 . B . # ") 9 $ A > 0
r 9 $ A 1 . 1 . . 1 - # ) r 7
r = R2
Model Summary M o d e l 1
R RS q u a re .900a .8 10
a . P r e d ic to r s : ( C o n s ta n t) , X
A d ju s te d RS q u a re .7 8 7
S td .E rro r o f th e E s tim a te 8 .8 2
K
C ? 0 D 2 E B " # H @
D E 1 # ) H !
R2 9 4 C + ' - B C # @ A 7 B # "
154
, S S T " % ) 1 N % 1 ? S S R = 9 ) % ) 1 N 9 4 ; 1 1
% # ! ! 1 3 - 1 E + Ad j u s ted R S q u a re L ! # ) ;
# , % 7 9 # (L ! G ) # ) 2 # 2 < D 2 . B
. 3 9 $ % $ > S ta n d a rd E rro r o f E s ti m a te " + ) E . # 9 1 $ ) / . !
C "3
) $ ' , 9 !
2 C " 3 # ! -
. $ - # $ . - .
yˆ # 1 S ca tterp l o ts $ - # $ < 1 $ ) / . # "
: ( 1 % . . # ! ? ) " + ) C " 3 e s ) / . ! , 6 G ra p h s S ca tter S i m p l e . $ 5 . S ca tter !
. S ca tterp l o ts
Y C D & Zre_ 1
5
. S PS S Vi ewer $ $ . . , 6 OK 4
5
. X C D & Pre_ 1
. S PS S Ch a rt E d i to r $ $ C # = . .
C Ref eren ce L i n e @ & Ch a rt Ref eren ce L i n e . $
: " . . , 6 . 0 ! #
5
5
5
1.5
1.0
.5
Standardized Residual
0.0
-.5
-1.0
-1.5 110
120
130
140
150
160
170
Unstandardized Predicted Value
# " % @ C " 3 # 0 ! # + . $ # $ 1 N 4 . 6 = - - $ ) E . 1 >
155
3 " $ B ) - 7 3 9 ! 1 . C "3 % 2= 3
:
C "3
y ) " # 1 , 1 $ . 1 < 1 $ ) / . # "
D 1
+ Pl o ts !
. . " ; . . C # ! 7 + ) C " 3 e s ) / . : " 1 , 6 L i n ea r Reg res s i o n !
Pl o ts 4
: "
5
) , % 2 ) + D E PE ND E NT # 1 2
) ( 2 1 ) / . " X & C (< " ; % F
!
O K 4 ! Co n ti n u e 4 3 Y & C Z R E S I D
" ! + B - > 0 C + $ - # $ . . (
Scatterplot
Regression Standardized Residual
1.5
: 1 . . # = D
Dependent Variable: Y
1.0 .5 0.0 -.5 -1.0 -1.5 110
Y
156
3 L i n ea r Reg res s i o n
120
130
140
150
160
170
180
C : . 1 (> ; " . ) $ ) / . I ) 1 . ? 4 1
N 4 / . E (-2, 2) M @ C "3 #
/ . % 95 % ) 2 ) / . ! # =
D (-1. 5, 1. 5) M M ) - ) / . 6 =
+ No rm a l p ro b a b i l i ty Pl o t . . (
. . J < ) 1 .
3 # . . ) 1 . N 4 / .
: 5 1 0 3 . . (
) 7 P l o t !
F $
Normal P-P Plot of Regression Standardized Residual 1.00
Dependent Variable: Y
Expected Cum Prob
.75
.50
.25
0.00
0.00
.25
.50
.75
1.00
Observed Cum Prob
/ . I ) 1 . ? 4 C " 3 # . ; 2 ? < 1 . 6 ) 6 =
. $ )
Weighted Least Squares Method ( 2 4 10 )
H o m o s ced a s ti ci ty $ ) E . 1 >
@ 3 . F
% 1 , 6 < Cro s s -S ecti o n D a ta @ ) ? . % 1 " $ F , 6 < 1 G
. 4 # =
Y Q # 4 ? 4 C K = , - 1 9 4 7 1 <= 6
1 !
7 Y # ? 1 ? < 1 ; < 1 - E . 1 E D " 3
Wei g h t 4
# W = 1 / y 2 1 3 var e = σ 2Y 2 " $ ) E . C = β 0 + β1Y + e
: ! E - B
W = 1 / Y 1 ) . L 1 $ ) E . 1 % 1 & 1
: B 1 7
C B0 e = + B1 + Y Y Y " ; B " $ ) E . 1 e 1 1 2 2 ; . $ ) E . " % 1 1 C " 3 " ! + var = var e = σ Y =σ2 Y Y2 Y2
157
" ) ? . # " ) % 1 ! 2 B0 B < 1 < % 1 ! 2
B1 6 =
B - " ! B ) F B ) ; 1 S PS S 5 1 H ) . F . % G S E E , R 2 ; 1 # " # 2 1 . G L S ) M ! % ) 1 . 1 < @
( 4 M ! % ) 1 . C " 3 ) : 4 #
# 2 .2 9 30 3 ) y Q # c K = , - # #
: ( ) 1 ; w ) " S PS S 5 1 D a ta ed i to r $ $ C c y w
10600 108 00 11100 114 00 117 00 12 100 12 3 00 12 600 13 2 00 13 000 13 3 00 13 600 13 8 00 14 000 14 2 00 14 4 00 14 9 00 15 3 00 15 000 15 7 00 164 00 15 9 00 165 00 169 00 169 00 17 5 00 18 100 17 2 00 17 8 00 18 5 00
1 >
12 000 12 000 12 000 13 000 13 000 13 000 14 000 14 000 14 000 15 000 15 000 15 000 16000 16000 16000 17 000 17 000 17 000 18 000 18 000 18 000 19 000 19 000 19 000 2 0000 2 0000 2 0000 2 1000 2 1000 2 1000
6. 9 4 4 4 E-09 6. 9 4 4 4 E-09 6. 9 4 4 4 E-09 5 . 9 17 2 E-09 5 . 9 17 2 E-09 5 . 9 17 2 E-09 5 . 102 0E-09 5 . 102 0E-09 5 . 102 0E-09 4 . 4 4 4 4 E-09 4 . 4 4 4 4 E-09 4 . 4 4 4 4 E-09 3 . 9 063 E-09 3 . 9 063 E-09 3 . 9 063 E-09 3 . 4 602 E-09 3 . 4 602 E-09 3 . 4 602 E-09 3 . 08 64 E-09 3 . 08 64 E-09 3 . 08 64 E-09 2 . 7 7 01E-09 2 . 7 7 01E-09 2 . 7 7 01E-09 2 . 5 000E-09 2 . 5 000E-09 2 . 5 000E-09 2 . 2 67 6E-09 2 . 2 67 6E-09 2 . 2 67 6E-09
: " ; ".
1 OL S 3 - M ! % ) 1 . 1 Y C " 3 C ) B .1
var e = σ 2Y 2 2 = ) 1 Y ? . 1 >
. 1 $ ) E .
G $ ) E . 1 (
1 .2
. - B 4 M ! % ) 1 .
. 217 .
158
1982
2
: #
2 1 # ) 1 % . > 0 1 OL S . 1 . 1 . - B .1 : B C # !
R 2 = 0.97 Cˆ = 1408.0 + 0.788Yd (4 4 9. 6) (0. 27) E . 1 > 3 " $ 1 - . ) " + ) E . # > 2 # 2 / . $ - # $ C " 3 Cˆ ) " ' 1 # 1 < 1 $ ) : % . ? 1 K 0 J S ta n d a rd i z ed Res i d u a l s + ) C " 3 )
L i n ea r !
L 0 . $ An a l yz e Reg res s i o n
$ ! S a v e !
" 5 1 (
L i n ea r
L 0 ! S a v e 4 Reg res s i o n
5
) Pred i cted Va l u es # U n s ta n d a rd i z ed S ta n d a rd i z ed $ ( Pre-1 E 1 $ $ , 6 ) D a ta ed i to r $ $ Cˆ ) !
. ( Zre-1 E 1 , 6 ) ) / . 5 1 (
) Res i d u a l s #
, 6 G ra p h s S ca tter S i m p l e . $
: " ! ; S ca tterPl o ts . Y-a xi s # C Zre-1 #
. X-Axi s # C Pre-1 # . OK 4
5
• • •
: " D A Ref eren ce L i n e @ A ) 1 . . , 6 3
2
1
Standardized Residual
0
-1
-2 -3
10000
12000
14000
Unstandardized Predicted Value
16000
18000
20000
E . 1 9 4 < 3 K 0 ! # 6 1 N 4 - $ - # $ . 6 = . , ) ; E . 1 > 3 " $ C $ Yˆ % 4 " $ )
159
1.
" var e = σ 2Y 2 2 = ) 1 Y # ? . 1 E . 1 ( 1 .2 ; 1 W = 1 / y 2 1 ; " 4
4 M ! % ) 1 . F = 3 # D a ta E d i to r $ $ C D @ A Tra n s f o rm ) 1 L i n ea r Reg res s i o n !
Co m p u te 1
, 6 7 . - / % . > 0 1 .
: " D 1
. WL S 4 ) 1 WL S Wei g h t W 4
# P 1 2 6 : B , 6 OK 4 3
5
Coefficientsa,b
M o d e l 1
( C o n s ta n t) Y D
U n s ta n d a r C o e ffic ie B S 1421.278 .79 2
d iz e d n ts td . E r r o r 3 9 5 .49 6 .0 25
S ta n d a r d i z e d C o e ffic ie n ts Be ta .9 86
a . D e p e n d e n tV a r ia b le : C b . W e i g h te d L e a s t S q u a r e s R e g r e s s i o n - W e i g h te d b y W
t 3 .5 9 4 3 1.5 11
S ig . .0 0 1 .0 0 0
: " 4 M ! % ) 1 . 1 9 ) 1
Cˆ = 1421.278 + 0.792Yd R 2 = 0.97 (3 95. 4 96) (0. 25) N 4 % 1 E " ) / . 1 2 = ) $ - # $ #
. $ ) E . 1 % 1 1 0 ! # . $ # $ 1
( 3– 4 10 )
: ! ) . B E y = β 0 + β1X 1 + β 2 X 2 + ... + β k X k + e
16 0
7
. % 1 # : β0 . 4 # Pa rti a l reg res s i o n Co ef f i ci en ts 4 - % = ) : β1, β 2 ,..., β k
. $ ) E . : e
" % 3 # K) P = K+1 ) . B ) 3 7
. (B
3 @ K C H @ . 1 B % @ , 0 ) . B % @
. (M u l ti co l l i n ea ri ty) " % 1 ) . . 1
1 ) x1 3 4 " ) 9 1 D a ta
y 6 8 8 7 7 12 9 8 9 10 10 11 9 10 11
? ( - H ) y 0 # @ #
: 5
$ $ % 1 % " 2 .19 8 13 15 x2 " " ) % . ( x1 9 10 8 7 10 4 5 5 6 8 7 4 9 5 8
: # E d i to r
x2 8 13 11 10 12 16 10 10 12 14 12 16 14 10 12
: ; " .
. 5 0 x2 x1 C " 3 y ) ;
. % = ) ) 1 ANOVA 1 # " #
. D W ! A 1 # " . 1 - " $ 1
!
, 6 An a l yz e
: % . ? 1 9 ; . 0
Reg res s i o n
L i n ea r
. $
: ; + L i n ea r Reg res s i o n
. D ep en d en t C D " Y
. I n d ep en d en t C , " X1, X2 $
. E n ter 3 - . - . N E M eth o d
. 17 2
16 1
.1
.2
.3 5
• • •
1982
3
7 Statistics !
, 6 L ine ar
Re g r e ssio n !
Statistics
: " # $ E 1
. % / ! & B ) : E stim ate : 5 (
.D W
.A N O V A R2 : M o d e l Fit
! A ; : D u r b in - W atso n
3 L ine ar r e g r e ssio n !
O K
4 3
Model Summaryb M o d e l 1
R .833a
RS q u a re .6 9 3
a . P r e d ic to r s : ( C o n s ta n t) , X 2 , X 1 b . D e p e n d e n t V a r ia b le : Y
A d ju s te d RS q u a re .6 4 2
S td .E rro r o f th e E s tim a te 1.0 1
D u r b in - W a ts o n .9 4 6
Coefficientsa
M o d e l 1
( C o n s ta n t) X 1 X 2
a . D e p e n d e n tV a r ia b le : Y
U n s ta n d a r d i z e d C o e f f i c i e n ts B S td . E r r o r 6.203 1.8 62 - .37 6 .133 .4 5 3 .120
S ta n d a r d i z e d C o e ffic ie n ts Be ta - .4 61 .615
t 3.331 - 2.8 34 3.7 8 6
S ig . .006 .015 .003
: " ) - B 1 ) yˆ = 6.203 − 0.376 X 1 + 0.453 X 2 R 2 = 0.64 (1.862) (0.133) (0.120) %1 1 3 4 " ) M 1 9 4 C $ X1 " )
9 4 X2 % 1 (
J X1 % 1 (
1 - 37 6 1 0 # ! C + ' " ) M
1 - 453 1 0 # 9 4 C + ' 9 " ) % . . B " . 9 C A $ R 2 2
SST " % - % ) 1 N # " 1 # " # ; (
E .
% ) 1 N SSR = 9 ) % ) 1 N C ∑ ( y − y ) 2 ) : @ 0 1 , 0 F ! A ; . SSE H 0 : β1 = β 2 = 0
H1 : β1 ≠ β 2 ≠ 0
: 1 # " # C " 3 # ! . B0 ? . " ) # $ - F 1 6 -
162
ANOVAb M o d e l 1
Re g r e s s i o n Re s i d u a l T o ta l
Su m o f Sq u a r e s (SSR)27.728 (SSE )12.272 (SST )4 0
a . P r e d i c t o r s : (C o n s t a n t ), X 2, X 1 b . D e p e n d e n t V a r ia b le : Y
d f (p - 1) 2 (n - p ) 12 (n - 1) 14
P-V al u e = 0.001< 0.05 2 . )
M e a n Sq u a r e (M SR) 13 .86 4 (M SE ) 1.0 23
F 13 .5 5 7 F = M SR/ M SE
Si g . .0 0 1a
# n ) 3 # P = 3 7
" + ) - + %5 - M 1 ) @ (
C 3
H " B2 B1 - " ) # 2 C " 3 9 - C " 3 + ) E , ) . 0 ! 3 < )
# ) t 1 C E " 0 9 ! 1 ) C " 3 # # E )
D " 3 %5 - M 1 X2 X1 # # " ) ) L @ D (C " 3 C o e f f icie nts . - B , 1 P 1 C ! ' =
1 %5 - M 1 $ ) / . I . 1 - 1 3 . $ ) / . ; . 1 C $ 1 D W
! A p = 3 n =15
( B # @ ? / . ) " $ 1 ) :6 #
2 % " X1, X2, X3 " % Y ) @ 4 # Y 43 63 71 61 81 44 58 71 72 67 64 69 68
X1 5 9 10 8 11 12 9 7 8 13 4 10 11
X2 3 5 7 4 6 5 4 7 5 8 5 9 10
X3 18 27 34 24 33 22 28 32 23 20 21 36 30
: " D ata E d ito r
X4 12 9 11 10 6 8 9 7 8 5 4 10 11
. ) . - )
. " % 1 M u l tico l l ine ar ity . ) " $ 1 . Ste pwise Re g r e ssio n ; " E 1 ) # @ : % . ? 1 # # 1 " . 0
.2 7 7 "
163
1988
.1
.2
.3
.1
! .
4
!
, 6 A nal y ze Re g r e ssio n
. $
L ine ar
5
: ; + L ine ar Re g r e ssio n
. D e pe nd e nt C D " Y $
. I nd e pe nd e nt C , " X1, X2, X3 % $
. E nte r 3 - . - . N E M e th o d
Statistics !
, 6 L ine ar Re g r e ssio n !
• • •
Statistics 4
" # $ E 1 7
5
. % / ! & B ) : E stim ate
.A N O V A R2 : M o d e l Fit
. . 1 - % = ) : Par t &
. . ) " $ R
: 5 (
Par tial C o r r e l atio ns
$ : C o l l ine ar ity D iag no stics
3 L ine ar r e g r e ssio n !
O K
4 3
Model Summary M o d e l 1
A d ju s te d RS q u a re .4 84
R RS q u a re .810a .6 5 6
a . P r e d i c t o r s : ( C o n s t a n t ) , X 4 , X 1, X 3 , X 2
S td .E rro r o f th e E s tim a te 7 .7 2
Coefficientsa
U n s ta n d a r d i z e d C o e f f i c i e n ts M o d e l 1
( C o n s ta n t) X 1 X 2 X 3 X 4
B
47.06 - .43 1.19 1.15 - 2 .03
a . D e p e n d e n t V a r i a b le : Y
0 9 3 8
S td . E rro r
13 .0
1.010 1.48 6 .476 .9 5 0
S ta n d a rd iz e d C o e f fic ie n ts Be ta - .104 .2 3 2 .63 1 - .462
t
S ig .
- .42 5 .8 07 2 .42 3 - 2 .1
.68 2 .443 .042 .064
3 .611
.007
Z e ro o rd e r
C o lli n e a r i ty S ta ti s ti c s
C o r r e la ti o n s
.2 10 .5 40 .63 4 - .3 3 1
P a r ti a l
- .149 .2 74 .65 1 - .604
P a rt
Tolerance
- .08 8 .167 .5 02 - .445
.713 .5 2 0 .63 3 .9 2 8
: " ) - B ) 1 yˆ = 47.06 − 0.43 X 1 + 1.199 X 2 + 1.153 X 3 − 2.038 X 4 R 2 = 0.48 (13) (1.01) (1.486) (0.476) (0.950) ! , 3 E $ 2 9 9 2 9 4 C $ X1 " ) 1 0 . > 0 1 . X3 X2
164
% 1 (
1 9 0.430 1 ) . B )
V IF 1.403 1.9 2 5 1.5 8 0 1.077
) % , 6 2 . X3 " ) t ! & P-v al u e 2 # = 6 = < 1
@ 0 L ! # ) 2 . (% 1 " ) C @ & 1 ) %5 - M 1
. 9 9 ! 1 . 2 = ) 3 1 ) - B C $ : " % . 1 - N = B
. ) # 1 1 . 1 . 1 - # ) : Z e r o -o r d e r C o r r e l atio n
% % 1 1 ) # ) 1 4 . 1 - # ) : Par tial C o r r e l atio n . (M "
% ) 1 1 # ) 1 / 4 . 1 - # ) :Par t C o r r e l atio n . . # 3 "
) " % # 1 4 % . 1 - ) ) - B
D " t ! & 2 C " 3 D D " 3 ) ? 4 . 1 # ) C " 3 D X3 6 =
. )
# 1 . 1 . 1 - # ) . 1 - B ) X4
# To l e r ance # ) ; 1 ) . . 1 - " $ R $ ( To l e r ance = 1- 7 " % # ) ? 1 # R 2 7 R2 X i .others X i .others
# # V I F # ) B . " % 1 i # 1 ) . 1 - 1 E < # ) 1 ) . VIF = 7 (V ar iance I nf l atio n Facto r ) Tolerance N 0 1 . ) " $ 4 ) # " ) 1 9 4 C " 3 " % 1 . 1 - G 1 t ! A 2 (
0 ) " ) , 6 3 1 B ) 1
5 3 4 " % V I F # ) 2 C " 3 # ! . (B < , 2
$ B % V I F 2 , . ) " $ 1 E " ) C $ 10
0 ! X ) . ) " $ R
, . ) " $ 1 , + E 3 C
$ X ′X 0 ! 9 4
) " $ C " 3 # , 0 ! 1 2 9 4 9 3 0 ( " %
C o nd itio n # 1 H ) # ) " % 1 . . 1 1 - . . <= 9 4 # C " 3
4 1 2 # ! ) 1 3 9 1 3 I nd e x
: " % 1 " # ;
Condition Index =
4.813 =1 4.813
: " ; X1 " 1 1
condition Index =
165
4.813 = 7.020 0.09868
3 % 4 A . . ) " $ A C " 3 $ ' , 15 3 # 2 % 4 A + 16 # " 2 1 6 =
1 1
# . " $ 9 . C " 3 $ ' , 30 . " $
# V ar iance Pr o po r tio n 1 H ) " $ " >
" $ 1 ) 7 4 # Pr incipl e C o m po ne nt . 1 0 < 1
? 0 C o nd itio n I nd e x # A 9 ' . )
> # . " % 1 9 ! 1
C " 3 1 # $ 1 9 ' . ) " $ 1 ) - , . X3 1 9 1 9 ! 1
: # L @ % 1
Collinearity Diagnosticsa
M o d e l 1
D im e n s io n 1 2 3 4 5
E ig e n v a lu e 4.813 9 .7 6 8E - 0 2 4.345E - 0 2 2.9 0 7 E - 0 2 1.6 6 9 E - 0 2
a . D e p e n d e n t V a r ia b le : Y
!
C o n d itio n In d e x 1.0 0 0 7 .0 20 10 .525 12.86 8 16 .9 83
V a r ia n c e P r o p o r tio n s (C o n s ta n t) X 1 X 2 X 3 .0 0 .0 0 .0 0 .0 0 .0 1 .0 6 .17 .0 0 .0 1 .7 1 .29 .0 8 .30 .0 5 .26 .22 .6 8 .18 .28 .7 0
X 4 .0 0 .35 .0 1 .6 3 .0 1
: " ) = 3 - % . ? 1 # 7 ; " . 0 , 6 A nal y ze
Re g r e ssio n
L ine ar
. $
: ; + L ine ar Re g r e ssio n
. D e pe nd e nt C D " Y $
. I nd e pe nd e nt C , " X1, X2, X3 % $
B # @ - % , 6 # 0 I D , M e th o d
• • •
:
. ( - 0 + 3 - ; " ) - B C " % # A : E nte r
) 1 ? B C A " " % . 1 ) 1 < % # A : Ste pwise
. % 1 1 9 ' G L 1 ! %
. B 9 9 . 1 , G % ) 1 : Re m o v e
. " " % . 1 ) 1 < 9 ' G % ) 1 : Back war d
L 1 ! % ) 1 - B C ) 1 < % # A : Fo r war d
. B ) 1 9 ' G
. ( . # @ 1 ) ) Ste pwise - . N
166
5
•
.1
.2
.3
.4
.5
Statistics !
, 6 L ine ar Re g r e ssio n !
Statistics 4
" # $ E 1 7
. % / ! & B ) : E stim ate O ptio ns !
. A N O V A R2 : M o d e l Fit
, 6 L ine ar Re g r e ssio n !
O ptio ns 4
: "
) 1 # A , 1 1 F 2 ) M C Ste pwise . B
: ; 1 K Ste pping M e th o d cr ite r ia # . B %
# & 9 . # + ) M : U se Pr o b ab il ity o f F •
) 1 - M # 2 ; % # & - M % ) 1
1 3 ) 1 - . E ntr y 2 4 B % @ . D % . Re m o v al 2 # " 2 B %
% ) 1 # & 9 . # + F 2 : U se F V al u e •
% @ . % ) 1 - F 2 C " 3 ; % # & F 2
2 4 B % 1 3 ) 1 - . E ntr y 2 # " 2 B . Re m o v al
+ Par tial F Te st 4 F 1 % ) 1 # 1 -
. 9 " ) ) 1 B ) / 4 ) 1
E $ 1 2 C # ! B C # , 0 @ % ) 1 N ) 1 -
1 # ) t 1 - < < F 1 - " 3 J B D 1 F ) 1
. . 9 " ) ) 1 - F
0.10 # O 0.05 + U se Pr o b ab il ity o f F # " @ - 3
. ) 1 =
167
: 5 (
3 L ine ar r e g r e ssio n !
O K
4 3
Variables Entered/Removeda M o d e l 1
V a r ia b le s E n te re d
V a r ia b le s R e m o v e d
X3
.
2 X4
.
a . D e p e n d e n t V a r ia b le : Y
S te P ro < = P ro e > S te P ro < = P ro e >
M e is e ( C b ility - o 0 , b ility - o = .10 0 ) . p w b a .0 5 b a
th o d r ite r ia : f-F -to -e n te r f-F -to -re m o v
p w b a .0 5 b a
is e ( C r ite r ia : b ility - o f- F - to - e n te r 0 , b ility - o f- F - to - r e m o v = .10 0 ) .
< " 3 B C ) 1 < ) 1 % # Ste pwise
. ; 1
. M % 1 D ) 3 % 1 A = % . ) 1 = @ 3 #
) ? . 1 . 1 # ) 1 D B C " % # X3
2 6 =
C o e f f icie nts = # . t ! & 2 1 1
, ( E ntr y # O - M ) 0.05 # 2 0.02 + t ! & P-V al u e
D " 3 ( 4 F 1 < a F " ) + t 1 6 - ) B C X3 # P 1 L
: " C 9 . B L 1 !
yˆ = 33.007 + 1.158 X 3
% 1 1 ) ? 4 . 1 # ) C " 3 D + # A 9 .
# ) D T ! A ; 1 ) E <- ; X4 X3
( E ntr y # O - M )0.05 # 2 0.033 + t ! & P-V al u e =
: # $ C " 3 L 1 ! B C X4 # P 1 L ,
yˆ = 46.152 + 1.345 X 3 − 2.147 X 4
1 + X4 X3 " t ! & # 2
- M ) 0.10 # 2 0.033 +
F = 3 B
X4 " % 2 t ! & P-V al u e
. B = C 1 , ( Re m o v al ) 1 =
X2 X1 @ - B # @ # , B F = 3 B
. 0.05 - M 1 ) 1 . 1 C " 3 D + ) , 6 7
. , B C # !
1 B 1 #
168
Coefficientsa
M o d e l 1 2
( C o n s ta n t) X 3 ( C o n s ta n t) X 3 X 4
S ta n d a r d i z e d C o e ffic ie n ts Be ta
U n s ta n d a r d i z e d C o e f f i c i e n ts B S td . E r r o r 33.007 11.6 4 8 1.15 8 .4 26 4 6 .15 2 11.011 1.34 5 .36 0 - 2.14 7 .8 71
.6 34 .737 - .4 8 6
a . D e p e n d e n tV a r ia b le : Y
( , ) B (2)
t 2.8 34 2.720 4 .19 1 3.735 - 2.4 6 6
S ig . .016 .020 .002 .004 .033
# B (1)
t2 1 E Ste pping M e th o d C r ite r ia U se F V al u e : 6 =
# 1 L
t2 > F (E nte r ) %
. B / 1 1 L
A # A ) ) 1 - # O F ! & 9
t2 > F(Re m o v e ) % A B A 3 . B C
: # # ) 1 % 1 # Excluded Variablesc
M o d e l 1 2
X 1 X 2 X 4 X 1 X 2
B e ta I n .027a .26 7a - .4 8 6 a - .012b .175 b
t
.108 .9 4 1 - 2.4 6 6 - .05 8 .721
S ig . .9 16 .3 6 9 .03 3 .9 5 5 .4 8 9
a . P r e d i c to r s i n th e M o d e l : ( C o n s ta n t) , X 3 b . P r e d i c to r s i n th e M o d e l : ( C o n s ta n t) , X 3 , X 4 c . D e p e n d e n tV a r ia b le : Y
P a r ti a l C o r r e l a ti o n .03 4 .28 5 - .6 15 - .019 .23 4
C o llin e a r it y S ta ti s ti c s T o le r a n c e .9 15 .6 8 2 .9 5 5 .9 09 .6 6 3
. = 9 . B C #
" ) " ) # Be ta in 7
169
Factor Analysis
( 1– 11)
3 ' Facto r s # ) 3 C " ) # " . H ,
Re spo nse
V ar iab l e s 1 - % 1 3 3 V ar iatio ns % = -
3 1 ) < 1 G Facto r s 9 # ) 3 9 $ % 3 1 ) 7
1 2 = ) 7 . 9 # ) L ine ar C o m po u nd s . ; 1 - %
. M # 3 % ? 2 = ) M 2
# ) # %
# " 2 3 # = K $ 1 . 1 - 0 ! ; , C " 3 3 " ) # "
. # )
Principal Components Method ( 211)
. E " ) # " . 9 % . Re spo nse
. , . 1
1 - % . ; 3 9 1 3 (# ) )
: " D 3 1 ) # E 1 - % p 1 3 1 . V ar iab l e s Z1 = a11 X 1 + a 21 X 2 + ....... + a p1 X p
. # # ) 1 1 - % L o ad ing s % ) 1 $ # aij 7
Z 2 = a12 X 1 + a 22 X 2 + ....... + a p 2 X p ( 1 - % % 1 # 1
: " D 3 1 )
1 0 ) V ar iance 1 6 3 D #
O r th o g o nal , 1 9 ) % F . ..… D " : . 1 % ;
1 - % V ar iance -C o v ar iance M atr ix
K $ 1 0 ! # )
.1
% . 1 - 0 ! # )
.2
. X − X 1 .
3 % - 1 D % E F
# ) F 1 - % C o r r e l atio n M atr ix > % H = < @
K Stand ar d ize d
V ar iab l e s ) % . 1 - %
: 1 #
17 0
r e g io ns . ; $ ) M 3 - % (
) 1 # % 1
5 1 D ata E d ito r $ $ , A ) 1 " , 6 19 7 7 ) (% 6 ) Re g io n g d p D o h o k 17.2 N ine v e h 24.0 A r b il 22.2 Su l ay m an 16.2 Ta' m e e m 32.3 Sal ah A L -D e e n 98.4 D ial a 23.1 A nb ar 22.7 Bag h d ad 75.0 W asit 19.5 Bab y l o n 22.8 K e r b al a 21.5 N aj af 18.7 Q ad isia 21.0 M u th ana 21.3 Th i-Q ar 18.1 M ay san 20.4 Basr ah 19.0 # l ite r acy 3 -
l ite r acy 30.1 44.2 35.2 33.5 49.4 37.9 44.1 44.3 61.6 36.7 44.1 47.7 46.2 35.2 33.5 33.8 34.4 53.6 %
h ig h e d u c 1.09 1.85 1.18 1.01 1.85 1.32 1.93 1.58 4.04 1.11 1.82 1.53 1.59 .95 .84 .73 .90 2.24 0 ; ! #
d o cto r s 17 14 13 10 18 15 10 16 36 28 18 24 27 9 18 12 11 25 ) # g d p
h o spb e d 139 172 163 115 143 80 153 144 280 199 145 173 190 195 178 144 301 219 7
: SPSS
" 3 9 , $ C " 3 " ! " 1 # h ig h e d u c 1 " ) " 1
9 3 # h o spb e d 100000 # / 1 . 3 # d o cto r s
. 100000 # % 0 $
. % . 1 9 % " % . 1 - # # " ; " . !
, 6 A nal y ze
D ata Re d u ctio n
: % . ? 1 K 0
Facto r
. $
: " D 1 + Facto r A nal y sis
.
17 1
Re g io n
: !
, 6 D e scr iptiv e s 4 3
5
: 2 @ +
Stand ar d
: " @ Statistics
J M e an # % " . 1 % ! & (
)1 (
.1
) : u niv ar iate d e scr iptiv e s
( ) J C o m m u nal itie s % $ = (
… D e v iatio n
) : I nitial so l u tio n
. 0 1 " 1 E ig e n V al u e s
9 J ) M J % . 1 - % = ) 0 ! !
, 6
(
) : C o r r e l atio n M atr ix
.2
E x tr actio n 4 3
5
.I nv e r se % . 1 - 0 ! > )
Facto r A nal y sis !
: " D 1 +
: # ! 0 ! @
@ ) % . # # " 1 " . . - : M e th o d
. ( " ) # " . . ) 1 5 1
< @
17 2
: " @ : A nal y se
K % " % . 1 - 0 ! # " : C o r r e l atio n M atr ix
. $ % " > % H =
3 % " K $ 1 1 0 ! # " : : co v ar iance
M atr ix
. > % > 0 , % K
: " (# ) ) % R
= - 1 " @ : E x tr actio n
1 ) < @ H ) , % R
= : E ig e nv al u e s O v e r
. ( + ; " G C " 3 ) 0 ) 2 3 4 ( 9 4
. 0 # 1 2 3 (# ) )% ) 3 R
4 = 4 % . ) C " 3 : M ax im u m Facto r M atr ix 9 G # ) 1 % % ) 1 $ (
. % . # )
= : N u m b e r o f Facto r s I te r atio n f o r C o nv e r g e nce
. # C # ! "
: " @ : D ispl ay
3 U nr o tate d f acto r so l u tio n C o m po ne nt M atr ix #
# + ! 2 # . . ( Ro tatio n !
, (
, 6 Facto r A nal y sis !
3 : Scr e e Pl o t
. E ig e n V al u e s
Ro tatio n 4 3
5
. 7 . C " 3 +
. # 1 2 D " 3 ! 9 ! % ) 1 $ 1 9 1 (L o ad ing s)% ) 1 $ # )
. 0 K - % - 0 ! % ) 1 $ 4 1 % ) 1 $ # "
J D ir e ct O b l im in J V ar im ax ) " . 5 1 . ? 1 $ " 1 9 $ O
3 + N o ne - $ # . ( Pr o m ax J E q u am ax J Q u ar tim ax Facto r Sco r e s !
, 6 Facto r A nal y sis !
.
Sco r e s 4 3
5
: "
: % 0 ! @
) Facto r Sco r e s# ) ; 1 5 1 $ E 3 : Sav e as V ar iab l e s D ata E d ito r $ $ 9 % C % F H @ ( % #
. ; 3 9 1 3 # Facto r Sco r e # ) < " 3
" # ) 3 ) i 2 ( ) # ) ; Z Sco r e s ) % : ) ; 1 ( p + % 3 1
17 3
p Fi = ∑ wij z j j =1
( j = 1,2,... p ) : 7
Facto r Sco r e s C o e f f icie nts # ) % = ) 4 # : w J ) % # : z
: $ E 3 , " 3 # !
. ! " # ) (
) 5 1 < " 3 D ispl ay Facto r Sco r e C o e f f icie nt M atr ix
. , = )
1 1 (A nd e r so n-Ru b in J Bar tl e ttJ Re g r e ssio n) . = 1 # ) ; :
. % = ) " D K 7 $ E 3 5 > 0 . ) = . E % "
% - ) 1 6 Facto r
) C o m po ne nts M atr ix
A nal y sis !
O ptio n 4 . 1
% 0 ! % ) 1 $ ; K 9 0 2 C " 3
. 0 # 1 2 2 3 " . , 2 # % = ) , 6 A 3 ; (< : 5 C "3 # !
Facto r A nal y sis !
O K
4 3
5
5
Communalities G D L IT H IG D O H O
P
IR A H E C T S P
C Y D U C O R S B E D
In itia l 1.000 1.000 1.000 1.000 1.000
E x tr a c tio n .7 9 7 .8 4 3 .8 9 6 .7 04 .7 7 2
E x tr a c tio n M e th o d : P r in c ip a l C o m p o n e n t A n a ly s is .
7 C o m m u nal itie s % $ = ! " # F = 3 #
% . 1 - 0 ! 3 % .
C ' % $ = R 2 # ) . 1 % 1 0 ! 3 # 1 % $ - '
. $ - ) C " 3 % 5
2 % 1 0.7 9 7 C $ <= G D P $ - ! "
1 ) 1 C 0 Q $ - 2 ( " 3 R
= ) $ # ) 0 G D P
(# ) )% ? G D P " Sq u ar e M u l tipl e C o r r e l atio n ) . 1 - # ) ? 1 3 1
# 2 7 % 1 3 1
3 C $ , % $ - 9 !
0 $ # ) 6 =
3 9 ! 1
2 C " 3 # ! . D o cto r s 0.7 04 . # " F ) 1 1 C !
1 + , 3 (% 1 ) % . 1 - 0 ! 1 #
1 ) 1 D # 7 % 3 1 5 + 0 ! : 7 3 - % " % 1
17 4
%58 0 2.9 00 + (
. %58 =
2 .9 = 100 * N / = # " 0 1 1 5
% 1 # %80.2 1
0 % 1 %22.2 0
.
3 # 0 < 6
% 1 5 1 # 2 J % "
Total Variance Explained In itia l E ig e n v a lu e s C o m p o n e n t T o ta l % o f V a r ia n c e C u m u la tiv e % 1 2.900 58 .009 58 .009 2 1.110 22.207 8 0.216 3 .523 10.457 90.6 7 3 4 .393 7 .8 6 4 98 .537 5 7 .313E - 02 1.46 3 100.000
E x tr a c tio n M e th o d : P r in c ip a l C o m p o n e n t A n a ly s is .
E x tr a c tio n S u m s o f S q u a r e d L o a d in g s T o ta l % o f V a r ia n c e C u m u la tiv e % 2.900 58 .009 58 .009 1.110 22.207 8 0.216
L o ad ing s % ) 1 $ @ C o m po ne nts M atr ix
% 0 ! # B
1 . 1 . 1 - # ) 3 9 1 3 ? 1 $ , ! = #
H I G H E D U C ) " ) # # ) 1 . 1 % M 2 . (# ) )
3 L I TE RA C Y " ) D " 0.941 # 1 ? 1 $ 7
9 3 G D P + # # ) 1 . 1 % H ) @ D O C TO RS / 1 . G D P , 1 . 1 % M 2 . H O SPBE D . % 1 1 0 ) @
% 0$
2 = ) 1 . 1 , > ) F 1 H O SPBE D S
Component Matrix a
G D L IT H IG D O H O
P
IR A H E C T S P
1 C Y D U C O R S B E D
C o m p o n e n t .477 .9 18 .9 41 .8 29 .5 0 8
2
.75 4 1.8 9 9 E - 0 2 .10 2 - .13 1 - .717
E x tr a c tio n M e th o d : P r in c ip a l C o m p o n e n t A n a ly s is . a . 2c o m p o n e n ts e x tra c te d .
:
$ ! " # ) 1 % ) 1 $ % ) 1 N $ .1 . % 2 1 0.477 2 + 0.754 2 = 0.797 + G D P
# !
17 5
<= " + (# ) ) 1 % % ) 1 $ % ) 1 N
: " # (# ) ) " C " 3 0.477 2 + 0.918 2 + 0.9412 + 0.829 2 + 0.508 2 = 2.9 . ; % " 3 ; 1 5 . 1 H = # ! 2 D 6 -
.2
; C o m po ne nt Sco r e s C o e f f icie nts (# ) ) % % = ) # B
# " G D P # ) <= C o m po ne nts M ar tix 1 % 0 ! % = ) F
0.477 = 0.165 2 2 2 2 2 0.477 + 0.918 + 0.941 + 0.829 + 0.508
: " ;
Component Score Coefficient Matrix
G D L IT H IG D O H O
P
IR A H E C T S P
1 C Y D U C O R S B E D
C o m p o n e n t .165 .3 16 .3 24 .28 6 .17 5
2
.67 9 .0 17 .0 9 2 - .118 - .64 5
E x tr a c tio n M e th o d : P r in c ip a l C o m p o n e n t A n a ly s is . C o m p o n e n t S c o re s .
: <= # " . ; 1 ; (# ) ) % 2
f ac_ 1 = 0.165*G D P+ 0.316*L I TI RA C Y+ 0.324*H I G H E D U C + 0.286*D O C TO RS+ 0.175*H O S PBE D + ) . ; Stand ar d ize d v ar iab l e s ) % # ) D < " 3 % C # ) H @ (... J L ite r acy J G D P % )
Re g io n
g d p
Dohok 1 7 .2 N in e v e h 24 . 0 A rb il 22. 2 S u la y m a n 1 6 .2 T a 'm e e m 3 2. 3 S a l a h A L -De e n 9 8 . 4 Di a l a 23 . 1 A n b a r 22. 7 B a g hd a d 7 5 .0 W a s it 1 9 .5 B a b y l on 22. 8 K e rb a la 21 . 5 N a ja f 1 8 .7 Q a d is ia 21 . 0 M u t ha n a 21 . 3 T hi -Q a r 1 8 .1 M a y sa n 20 . 4 B a sra h 1 9 .0
l ite r acy 3 0 4 4 3 5 3 3 4 9 3 7 4 4 4 4 6 1 3 6 4 4 4 7 4 6 3 5 3 3 3 3 3 4 5 3
.1 .2 .2 .5 .4 .9 .1 .3 .6 .7 .1 .7 .2 .2 .5 .8 .4 .6
, 0 + , > ( 6
: " D ata E d ito r $ $ 9 h ig h e d u c d o cto r s h o spb e d f ac_ 1 f ac_ 2 1 .0 9 1 .8 5 1 .1 8 1 .0 1 1 .8 5 1 .3 2 1 .9 3 1 .5 8 4 .0 4 1 .1 1 1 .8 2 1 .5 3 1 .5 9 .9 5 .8 4 .7 3 .9 0 2. 24
1 7 1 4 1 3 1 0 1 8 1 5 1 0 1 6 3 6 28 1 8 24 27 9 1 8 1 2 1 1 25
1 3 9 1 7 2 1 6 3 1 1 5 1 4 3 8 0 1 5 3 1 4 4 28 0 1 9 9 1 4 5 1 7 3 1 9 0 1 9 5 1 7 8 1 4 4 3 0 1 21 9
-. 8 4 8 7 3 . 0 5 26 5 -. 6 5 4 5 8 -1 . 1 0 9 3 9 .3 7 0 9 7 -. 1 1 3 6 2 -. 1 4 0 1 4 -. 0 8 3 0 3 3 . 227 4 8 . 0 4 7 21 . 0 9 229 .4 1 8 3 9 .5 3 7 0 8 -. 8 1 0 1 3 -. 6 28 6 9 -1 . 0 3 0 5 2 -. 4 4 1 3 9 1 .1 1 4 1 5
) % % < " 3
.0 0 8 6 2 -. 0 1 0 9 1 -. 0 4 0 9 5 .3 7 6 5 7 .5 4 5 0 1 3 . 3 25 0 0 . 26 3 9 1 . 223 1 4 . 21 8 5 0 -. 8 0 4 5 7 . 21 0 6 6 -. 29 1 3 3 -. 6 27 7 1 -. 4 29 0 6 -. 3 7 4 23 . 0 20 27 -1 . 7 6 8 8 6 -. 8 4 4 0 6
% 9 & J - B . ) " $ ) <= ! % - )
17 6
0 ! " . 1 ) % (# ) ) % . 9 $ % - (# ) ) ? # ) 2 1 ) D " ) ) 1 . ? 4 ? 1 # ) F % " + ) H
. 9 $ < 2 (-2, 2) M B
% - 3 # ! " " Scatte r Pl o t $ - . . Scatte r !
: % . ? 1 . . . 9 $
, 6 G r aph s
Scatte r (Sim pl e ) . $
. Y A x is : f ac_ 2 H 3
. L abe l C as e s by : R e g io n
. Pl o t
. X A x is : f ac_ 1 H3
C h ar t $ $ 2 . $ C h ar t
. OK 4
F , 6 3)
R e f e r e n ce L in e
: . . , 6 ( 0 ! 3 Y A x is X A x is # Ed it o r
4
Salah AL-Deen
REGR factor score 2 for analysis
1
3 2 1
Ta'meem Sulayman Diala Anbar Babylon Thi-Qar Dohok Arbil Nineveh Kerbala Muthana Qadisia Najaf Wasit Basrah
0 -1
Baghdad
Maysan
-2 -3 -4
-4
-3
-2
-1
REGR factor score 1 for analysis
0
1
2
3
4
1
$ - # $ . E ) 1 . ? 4 ; (# ) ) % " - ? 4
@
? . 6 =
9 $ ! . (0, 0) . # + # $ 1 N 4
(3 ; ) # # ) " 9 $ 2 , 1 6 C . 3 (-2, 2) M
% (
(< @ 3 ; ) # ) " 9 $ 2 , Q = !
6
. ? 6 % 1 1 ( ) 6 " 9 $ 3 '
% = K E 1 6 1 1 J # ) 9 1 % ) 1 $ % % " % 6 6 % 2 % 2 d o ct o r s h ig h e d u l it e r acy # # ) 1 3 1 ? 1 $
# K 1 . % 6 ) % F .
1 C " 3 1
.(3. 227 )# # ) " 1 6 9 1 2 C " 3 # ! ; 1
17 7
Case Summaries Statistics: Mean
L IT IR A C Y 6 1 .6 0 4 1 .4 2
B ag h d ad T o tal
(
H IG H E D U C 4 .0 4 1 .5 3
D O C T O R S 3 6 .0 0 1 7 .8 3
+ ) G D P ) C ? Q = !
6 (3. 325) 9 $ ; 1
0 G C " 3 % 6 . ? 1 ( 1 3 1 ? 1 $
1 3 1 ? 1 $ - . . 1 1 6 HOSB ED
: # , @ . ( C o mpo n e n t s M at r ix % 0 ! 6 ) 1 9 $ 1
Case Summaries Mean S al ah A L - D een T o t al
G D P 9 8 .4 0 2 8 .5 2
H O S P B E D 8 0 .0 0 1 7 4 .0 6
P 1 " Eig e n 0 ! #
V =
: % 6 =
V e ct o r ( 4 ) D C " 3 # !
X 12 + X 22 + ... + X n2 ) ; NOR M
.1
D # .
# ! " No r m # . C " 3 (? 1 $ ) 2 2 # 1 K C o mpo n e n t s M at r ix
Un iq u e
D D . + No r mal iz e d V e ct o r + ) D C " 3
: " # # ) 1 G D P ? 1 $ # D " C ; <= V e ct o r 0.477 = 0.280 2 2 2 2 2 0.447 + 0.918 + 0.941 + 0.829 + 0.508
(2.9) # " # , # #
G D P
L I TER A C Y
HI G HED UC
D OC TOR S HOSPB ED
Eig e n V e ct o r 1
Eig e n V e ct o r 2
0.538845
0.018025
0.280278 0.552474 0.486656 0.29 83 7 8
. % . 1 - 0 ! (1.11)
0.715757 0.09 6 4 7 4
-0.12474 -0.68007
; @ # ! + Or t h o g o n al , 1 9 ) % # ! N +
178
fac _ 1, fac _ 2 = ∑ fac _ 1 * fac _ 2 = 0 0 !
.2
+ , D o t Pr o d u ct
% % = ) , # ; @ # ! E K . " " 1 ; @ . 0 !
+ , C o mpo n e n t s Sco r e C o e f f icie n t s
Factor Analysis Methods ( 3 – 11 )
/ 1 . 1 ) " ) # " . 9 % .
. ; - @ < 1 " ) , E 1 . 1 1 4 M . E 1 " ) # " " ) # " B , 3 1 ) 3 9 ! 1 " ) # " .
F act o r A n al y s is
# ) 3 X1, X2….Xp 1 - % # 3 1 ) + M o d e l . K 1 R
# 3 C o mmo n F act o r s ( 1 - % ) $
: " " ) # " B 1 - % ) 1 . ? 4 ( X 1 = a11Y1 + ............. + a1mYm + e1
1
......................................................... X p = a p1Y1 + ........... + a pmYm + e p
7
. ( p 1 - % 3 # 2 m # ) 3) j K $ # ) : Y j
. i 1 - ; j # ) > ) ) L o ad in g s % ) 1 $ : aij . ( Spe cif ic F act o r ) Xi 1 R
(M ax imu m L ike l ih o o d
# ) : e i
M e t h o d 6 3 & . C " 3) : 2#
, . 1 ) 6 3 & . 1 " ) # " / # 1 # % 1 . N
. % . . F 1 H= - D " ) # "
3 # # , $ , 0 % . 1 1
% , 6 7 F act o r A n al y s is : Ex t r act io n !
M ax imu m L ikl e h o o d
:
F a c to r A n a ly s is Communalities G D L IT H IG D O H O
P
IR A H E C T S P
C Y D U C O R S B E D
In itia l .350 .8 52 .8 7 0 .503 .2 8 6
E x tr a c tio n M e th o d : M a x im u m
E x tr a c tio n .9 9 9 .9 03 .9 35 .4 8 7 .2 2 7 L ik e lih o o d .
< % . 1 1 in it ial C o mmu n al it ie s
+
R
2
% ) 1 $
) . 1 - # ) ? 1 + ? 1 $ E " ) # " . 2 1
I n d e pe n d e n t ) % 1 C " 3 ( D e pe n d e n t V ar iabl e ) D " 3 # !
0 # ! " " ) 1 G D P 1 - 0.9 9 9 . (V ar iabl e s . G D P " " % = - 0. 9 9 9
179
Total Variance Explained F a c to r 1 2 3 4 5
T o ta l 2.900 1.110 .523 .393 7 .313E - 02
%
In itia l E ig e n v a lu e s o f V a r ia n c e C u m u la tiv e % 58 .009 58 .009 22.207 8 0.216 10.457 90.6 7 3 7 .8 6 4 98 .537 1.46 3 100.000
E x tr a c tio n M e th o d : M a x im u m
L ik e lih o o d .
, " 3 " ! , 0 I n it ial R
Eig e n v al u e s 1 F = 3 #
" % ) 1 $ % ) 1 N 6 =
1 1
E x tr a c tio n S u m s o f S q u a r e d L o a d in g s T o ta l % o f V a r ia n c e C u m u la tiv e % 1.413 28 .254 28 .254 2.138 42.7 56 7 1.009
% . % .
M K I n it ial e ig e n v al u e s D 0 Ex t r act io n Su ms Sq u ar e d L o ad in g s
0 1 1 # R
! " 1 H= 6 3 & . 0
" # ) % ) 1 $ % ) 1 N ; <= F = 3 # L @
: " F # ) 0 ! 0.999 2 + 0.333 2 + 0.469 2 + 0.275 2 − 8.71E − 02 2 = 1.413 1.413 / 5*100 = 28.254% # # ) F 0 1
Factor Matrixa
G D L IT H IG D O H O
P
IR A H E C T S P
1
C Y D U C O R S B E D
F a c to r
.999 .3 3 3 .4 6 9 .27 5 - 8 .7 1E - 0 2
2 - 9.4 9E .8 .8 .6 .4
0 3 90 4 6 4 1 6 8
E x tr a c tio n M e th o d : M a x im u m L ik e lih o o d . a . 2 f a c t o r s e x t r a c t e d . 14 i t e r a t i o n s r e q u i r e d .
1 # % 0 ! R
> 0 , ! " # ) 0 ! F = 3 0 !
Goodness-of-fit Test C h i- S q u a r e 1.337
d f
1
S ig . .2 4 7
% 1 # # ! " # ) 1 " ) @ 0 1 # F = 3 #
2 . % 1 # # ! " # ) 0 ) 1 " " 1 @ 0 @ (% . 1 ) ) @ # 1 2 C 3 P-v al u e =0.247 2 7 χ 2 ! ( , %
180
% % 1 # # ! " " ) 0 1 " + % 5 % 1 - M 1
. % . G 1 - . 1 - : 6 =
% . % " 1 1 # F act o r Sco r e s # ) %
% . 9 . 1 ; F act o r s co r e s C o e f f icie n t s % = ) ) 1 -
. 3 K , 6 3 & . 1 1 (# 3 ) K , ,
3 . F , 6 ) " . F
# ) " # 1 = C " 3 # !
: ( F act o r A n al y s is !
# ) 1 ) . 1 - # ) ? 1 + 1 0 ! . # 2 ! # ) % ) 1 N 0 !
0 !
181
, # ) % = ) Sco r e s 4
. , # ) : R e g r e s s io n
. # ) 9
+ . , # ) : B ar t l e t t
+ . , # ) 7 1 B ar t l e t t . : A n d e r s o n -R u bin s
. ( . 1 G ) " # ) + + ) H
Non Parametric Tests
" ) ? ) C " 3 , 1 - ! A ) - % 1 " ) = % 1 -
@ H ) , , % 1 " ? 4 (
0 - , V ar ian ce 1 M e an
.
C ) " ) = % 1 - # ) ; 1 . D is t r ibu t io n – F r e e t e s t s ? 4 % 1 1
? 4 < 1 2 ? % 1 N 4 ; <= " ) % 1 - 1 ! % @ 0 3 E " . $ 3 3 # ) - ) $ " ) % 1 - T 1 1 . 3 ) 1 .
. $ 1 # , , ; . $ , 9 F < " 3 " ) = % 1 - C
, , 1 ! . $ " ) % 1 - # ) ; D " ) % 1 - " " ) = 1 - . < < 1 < 3 SPSS 5 1 . . " ) = % 1 - 2 . % 1 - F (
Obs e r v e d
) 1 0 0 L @
C h i -Square ( 1 12 )
f r e q u e n cie s % 0 " $ 1 " C h i-Sq u ar e 1 # )
% E . ) @ > C " 3 ; Ex pe ct e d F r e q u e n cie s , ? 2
+
: " C . ) 1 - " ) C h i-Sq u ar e ! E K 3 k (Oi − Ei ) 2 2 = χ ∑ Ei i =1
1 - ? 2 # Ei $ # Oi 7
: % 0 ! C " 3 # ! ) $ 0 ! , 1 Oi t y pe 439
16 8 133 6 0
. 3 75
8 0 0
1
3
2 4
1979 : % 5 - M 1 ) @ 1 ; " .
H 0 : P1 =
182
9 3 3 1 , P2 = , P3 = , P 4 = 16 16 16 16
. k-1
:1 #
0 ! 1
# P1 <= ) ; F 3 H" 5 C " 3 R : % . ; C h i-Sq u ar e 1 1 .
t y pe 1 2 3 4 4
H1 " 1 @ 0
. ( 0 1 C
9 @ 0 1 -
: " D at a Ed it o r 2 % 1 ;
Obs e r v e d 439 168 133 60 % ? # ) A ) Ty pe + ) 1 % 0 ! 3 @ ) 6 -
C V al u e Obs e r v e d
L abe l 3 @ A & 1 D " ) ? % 0 ! / A 3 +
. " " 2 <- 1 % # 3 (
) Ty pe
. 3 K % - " 4 E 2 # ) # $ #
!
W e ig h t C as e s by $ ' ) 1 . $
D at a
W e ig h t C as e s
. (W e ig h t C as e s by ) C Obs e r v e d # A W e ig h t C as e s
, 6 A n al y z e
No n par ame t r ic Te s t s
C h i-Sq u ar e
. $
: " D 1 + C h i-Sq u ar e Te s t !
. t e s t V ar iabl e L is t C Ty pe " 6 -
: Ex pe ct e d V al u e s
. 1 > 0 , ? 2 > 0 , % 0 ? : A l l cat e g o r ie s e q u al
C ( ; H" 1 ) ? 2 H" 3 $ E : V al u e s
: " ) @ 9 ; % " # # M 9 ; V al u e " # . P1 = = 0.5625 C # 16 . ( 2 1 / $ > 0 ) v al u e " # 0 H @ A d d 4 ) 1 0. 5625 : 5 C "3 # !
183
OK 4 3
.1
.2
TYPE 1 2 3 4
T o ta l
O b s e rv e d N 439 16 8 133 6 0 8 0 0
E x n p n p n p n p
p e c te d N 1 45 0 2 15 0 3 15 0 4 5 0
R e s id u a l - 11. 0 18 . 0 - 17 . 0 10 . 0
" # N " ) 2 ; <= ) 2 9 $ # F = 3 #
D 0 ) 2 " ) E D " 3 1 + ; N 6 - n P1=800*0.5625=450 9 $ "
.
Test Statistics C h i- S q u a r e a d f A s y m p .S ig .
T Y P E 6.356 3 .0 9 6
a . 0 c e l l s ( .0 % ) h a v e e x p e c t e d f r e q u e n c i e s l e s s t h a n 5. T h e m i n i m u m e x p e c t e d c e l l f r e q u e n c y i s 50 .0 .
P-v al u e 2 6. 356 + C h i-Sq u ar e ! A 2 E F = 3 #
) @ 9
; # 1 2 + % 5 - M 1 ) @ # 1 2 C 3 0.096
!
< 1
1 3 1
? 4 # ) Tr an s f o r m
C o mpu t e P-V al u e B K . : + ? 1
1-C D F .C HI SQ (6.356, 3) =.096
: 2 #
5 % He ad ! 3 % 1 9 # 9 1 0 0 0 ? . 2 %
: ( D at a Ed it o r 2 , A ) 1 )
h e ad n o o bs e r v e d 0 38 1 144 2 342 3 287 4 164 5 25 ? 4 ? 1 9 ! , 6 % 3 E 1 " @ 0 1 C h i-Sq u ar e 1 1
. % 5 - M 1 B in o mial
# 1 . G o o d n e s s o f F it 1 . 1 1 H) C h i-Sq u ar e 1
: % . ? 1 1 # ) 1 . > 0 1 Obs e r v e d 1 % - ( 4 )
A n al y z e No n par ame t r ic Te s t s
C h i-Sq u ar e
. $
: " D 1 + ( 1 # " D 0 ) C h i-Sq u ar e Te s t !
184
, 6
. Te s t V ar iabl e L is t C h e ad n o #
% C 0 !
9 ! , 6 # ; bin o mial ? 4 # )
•
: " 5
No . o f h e ad s 0 1 2 3 4 5
•
9 F = 3 (% - - ) ; # Ex pe ct e d
Pr o babil it y 0.03125 0.15623 0.3125 0.3125 0.15623 0.03125 v al u e s v al u e s : 5 C "3 # !
•
. M ) 1
OK 4 3
5
HEADNO
O b s e rv e d N 38 144 342 287 16 4 25 1000
0 1 2 3 4 5
T o ta l
E x p e c te d N = 1000* P r 31. 2 156 . 2 312. 6 312. 6 156 . 2 31. 2 1000. 0
R e s id u a l 6 .8 - 12. 2 29 . 4 - 25. 6 7 .8 -6 .2
: " (0 ! + ! 3) <= C 0 " ? 2 B Ex pe ct e d F r e q u e n cy .= 1000*0.03125=31.25
Test Statistics C h i- S q u a r e a d f A s y m p .S ig .
H E A D N O 8.920 5 .1 1 2
a . 0 c e l l s ( .0% ) h a v e e x p e c t e d f r e q u e n c i e s l e s s t h a n 5. T h e m i n i m u m e x p e c t e d c e l l f r e q u e n c y i s 3 1 .2.
! 3 + % 5 - M 1 ) @ # 1 2 C 3 P-v al u e =.112 2
. B in o mial ? 4 ? 1 $
0 # , 1 # 0 % 0 <- 1 % 0 M
: 6 =
0 F (5S1= ! 3) 1 > % 0 1 0 (0 = ! 3)C
C h i-s q u ar e
!
Ex pe ct e d V al u e s (5S1) . % 0 F , % - - 4 1
# - H 1 - 1 # (6S0) ! ) " 1 % - - " 2 Te s t
185
4 Ex pe ct e d
V al u e s 0. 03125 + # - $ E 1 0= ! ) # 1 . R e mo v e
% 0 M 1 (5S1) % 1 % 0 1
Ex pe ct e d
Uppe r 2 1 + L o w e r 2 # A Us e Spe cif ie d R an g e $ E 1 R an g e : C "3 # !
OK 4 3 J 5 +
Frequencies C a te g o ry
1 2 3 4 5
T o ta l
1 2 3 4 5
H E A D N O O b s e rv e d N E x p e c te d N 144 155. 1 342 310 . 4 28 7 310 . 4 16 4 155. 1 25 31. 0 9 6 2 9 6 2
R e s id u a l - 11. 1 31. 6 - 23. 4 8 .9 -6 .0
Two Independent Samples tests ( 2 1 2 )
T 1 # ) 7 " 3 . T 1 - 1 % 1 - F
? 4 . $ ) 1 - # ) - K 3 T ? 4 ? 1 1 - ! A
% 1 - SPSS 5 1 7
" ) = % 1 - C E " K ) ) ) 1 .
: ") =
M an n -W h it n e y U 1
.1
M o s e s Ex t r e me R e act io n s 1
.3
Ko l mo g o r o v -Smir n o v Z 1
(1 , 4 )/ ! R
D < " 3 G r o u p , @ R
W al d -W o l f w it z R u n s 1
.2
.4
$ I 8 1 C " 3 # % 1 : 3# $ 3 (24 )C @ R
$ I 10 1
d s e as e ) , " 1 2 He al t h y ) , " 1 1 ) , V al u e L abe l @ A
, R
% 2
> 2 2 ( B & # 3 <- 1 ) , 6
D at a Ed it o r $ $ " % 1 , 6 ) R t im e
10 14 6 8 4 8 10 9 9 0 8 4 0 9 7 8 10 0 2 1110 8 6 4 6 3 6 6 3 8 7 0 8 7 8 6 6 0 0 13 20 7 5 0 5 9 4 7 5 0
186
g ro u p 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2
$ # ( Time ) : SPSS 5 1
% 5 - M 1 ? > 0 1 ) E 1 " ) @ 1 ; " .
" 1 @
µ1 = µ 2 ) @ 0 1 C ) 1 ) M an n -W h it n e y 1 1 . ( µ1 ≠ µ 2 : % . ? 1 K 0
A n al y z e No n Par ame t r ic Te s t s 2 I n d e pe n d e n t s ampl e s . $ :
!
2 I n d e pe n d e n t s ampl e s Te s t , 6
Te s t V ar iabl e L is t ( ) % $ # + ) Time " 6 3 H ) 4 G r o u pin g C @
V ar iabl e G F " g r o u p
3 G r o u p1 : 1 / ! 3 H3 D e f in e G r o u p 4
. M an n -W h it n e y U 1 $ E < . G r o u p2 :2 : 5 , 6 OK 4 3
Ranks T IM E
G R O U P h e a lth y d s e a s e T o ta l
N 1 0
8
1 8
M e a n R a n k 1 2 .6 3 7 .0 0
S u m
o f R a n k s 1 0 1 .0 0 7 0 .0 0
9 3 (C @ / ! ) ) 5 7 R an ks ; C " 3 1 - )
; N ) 3 # ; N 2 # 1 / . 3 < 3 ! ) 2 ; ;
187
F = 3 # ( 7 0 C @ ; N 101 / !
: ! 1 M an n -W h it n e y U ! A N ( N 1) U = N1 N 2 + 1 1+ − T1 2
M - ) # N2 ( N1=8 C , ) ) + # N1 7
# .( T1=101) Su m o f R an ks C ) ; N # T1 (N2=10 )
! A C @ & 1 C ) % . ) C " 3 3- 1 1 U ! A 2 + U ) ? 4 ) ; Z 2 B - .U ! & W il co x o n W
: " ? 4 " + ) H - . B 7
µ=
N1 N 2 = 40 2
σ =
N1 N 2 ( N1+ N 2 + 1) = 11.25 12
B D " 3 < 1 ) " ) 1 . ? 4 ; U ) ? 4
" ) 1 . ? 4 " )
P-V al u e 2 B K Z = (U − µ ) / σ = (15 − 40 ) / 11 . 25 = − 2 .222 # ) 1 Tr an s f o r m
C o mpu t e 1 Z ! &
- M 1 ) @ (
C 3 1 ) 1 . ? 4 " P-v al u e =0.026 2 7
( . 1 - ) 2*C D F NOR M (-2.222)=0.0263
" ) 1 . ? 4
% 2
. ? > 0 1 ) + # 1 ( . C @ R
$ I % 2
. 3 < H" / ! R
0 1 % 5
$ I , R
Test Statisticsb M a n n -W h W ilc o x o n Z A s y m p .S E x a c t S ig S i g .) ]
W
itn e y U
ig .( 2 - ta ile d ) . [ 2 * ( 1- t a i l e d
T IM E 15.000 7 0.000 - 2 .2 2 2 .02 6 .02 7
a
a . N o t c o r r e c te d fo r tie s . b . G r o u p in g V a r ia b le : G R O U P
U # - 1 . # 2 / U # - . ( / 0 T2 # & # ' ( ) * * + , : # $ % : "
N 2 ( N 2 + 1) − T2 2 1 - / U ! & ) B 1 9 1 ) # N2 U = N1 N 2 +
. 1 > 0 C # !
K- Related Samples Tests K ( 3 12 )
1 " ) T 1 - " ) - . On e - W ay A NOV A
M an n -W h it n e y 1
) 1 # " " ) - 1 Kr u s kal l -W al l is
T 1 - 4 = . $ 3 K T 1 # ) G 3 1
188
" ) = % 1 - / F R an ks ; 3 9 1 3 % 1 : SPSS 5 1
. F r ie d man 1
. Ke n d al l ’s W
. C o ch r an ’s Q
1 ) c b a 1 , % 4 0 " B = ; R D at a Ed it o r $ $ , 6
5
.3
: 4 #
b 3 3 3 3 2 2 3 3 3
)
c : SPSS 5 1 1 1 1 2 1 3 1 2 2 1 " ) @ 1 ; " .
. % 5 - M 1 F r ie d man 1 1 : % . ? 1 K 0
No n par ame t r ic Te s t s K-R e l at e d s ampl e s
. $
: " D 1 + Te s t s f o r s e v e r al R e l at e d Sampl e s !
D an ie l W .W .(1978) , B io s t at is t ics : A Scie n ce s , 2nd Ed it io n , pp.398 .
189
1
.2
! 1 Th e r apis t s ! ) 2
: 5 C "3 # !
5
1
5 % ( 3 2 1 , " C # @ 0 C 1 $ 1
Th e r ap a 1 2 2 2 3 2 4 1 5 3 6 1 7 2 8 1 9 1 = B " # @ 0 ) % 2
A n al y z e
.1
F o u n d at io n
, 6
OK 4 3
f o r an al y s is in
Th e
5
5
He al t h
N P a r T e s ts F r ie d m a n T e s t Ranks A B C
M e a n R a n k 1.67 2 .78 1.5 6
# " D 1 $ F = 3 1 . = B # ; . # M e an R an k 7
R an d o miz e d
$ ) % 3 . ! 1 H ) Tw o - w ay A NOV A
) 1
# H 0 ! Tr e at me n t s % ) (B ) 9 3 # 7 B l o cks Ex pe r ime n t
; ; ) 1 # " / < = F r ie d man 1 1 ) 7
B l o cks % 3 .
? 1 F r ie d man ! A # 2 Or d in al 1 % 1 ; " . R an ks : " ; J-1 1 χ 2 ? 4 χ2 =
12 ∑ T 2 − 3K ( J + 1) = 8.2 KJ ( J + 1) i
(
# Ti (9 3 ) % ) 3 # J (%3. ) H 0 ! 3 # K 7
. J=3 K=9 + ) # ; N
C 3 P-V al u e 2 F r iedm an ! A 2 1 F #
. = B " # @ 0 ) <2 K + % 5 - M 1 ) @
Test Statisticsa N
C h i- S q u a r e d f A s y m p . S ig .
a . F r ie d m a n T e s t
190
9 8 . 222 2 .0 1 6
(
CHARTS
3 , . 1 0 !
/ ! & % , 9 1 %.. 1 )
. . B ar s 1 9 3 , %.. . 9 1 ) . 1 .1 ! & % 1 %= , % & (
)
# ! 0 # …dPies 1 Lin es 1 . 1 ) # S PS S 5 1
Bar Charts ( 113) : 1 #
y ear 1990 1991 1992 1993 1994
: Y ear % ; % ' M & S al es %) 1 1 # s al es 5 0 5 2 5 5 6 0 6 5 . B ar C har t 1 9 3 .. 3 ;" .
2 B ar C har t !
: % . ?1 K 0
, 6 .G r ap hs B ar . $
.
: F 1
F # # 1 Data in C har t ar e 2 V al u es o f in div idu al cas es 2
. %- . 1 S im p l e 2 S tack edJ C l u s ter ed J S im p l e % =
Defin e S im p l e B ar !
191
, 6 1 !
Defin e 4 3 : D 1 +
: 7
.
. .. . $ 1 # D 2 2 # + 3 : B ar s R ep r es en t
: " @ ( ) 1 .. " % 0 3 : C atego r y Label s . C " 3 " ) 2 (
) : C as e n u m ber
) C " 3 ) F 2 (
) : V ar iabl e
. ( Y ear s #
. F o o tn o te , s u btitl e,d Titl e .. 3 (
) :Titl e
. M %.. 3 3 <9 $ 1 , 1 . ) %0 ! + ; 2 # ) :Tem p l ate : " S PS S V iew er .. (
T itle L in e 1 Line2 Subtitle
F o o tn o te
192
3 O K 4 3
1 2 ..
Establishment Sales by Years for Period 1990-1994 70
Value SALES
60
50 40
1990
1991
1992
1993
1994
YEAR
Iraqi Dinars (Thousands) . . (
) 7 > 4 1 F 1 .. C " 3 %= ) / S PS S C har t E dito r
: " S PS S C har t E dito r
C har t E dito r $ $ - M %= ) ) %= ) / 7
: ( > 4 1 .. ) 1 +
C har t E dito r $ $ + %= ) ) " K 0 : 9 3
: (F = 3 # $
F o r m at C o l o r
193
. > 4 1 9 3
C har t E dito r $ $ . $
.1
: " C o l o r s !
, 6 % . $
: 7
. . $ / = A
: F il l
. . $ "
: B o r der
> 4 1 F 1 4 " <= 4 " C . $ / = A
9 3
) 1 .. , 6 . C o l o r s !
. 9 3
A p p l y 4 F il l $ E E ) 1 " C l o s e
4
: "
2 2 .. Establishment Sales by Years for Period 1990-1994 70
Value SALES
60
50 40
1990
1991
1992
1993
1994
YEAR
Iraqi Dinars (Thousands)
:
0 " 1 7 C 9 . 3) 1 % . > 0 1 <= 0 "
. (9 3 <- 1 ..
: " ?1 K 0 : B ar S ty l e 9 3 .
F o r m at B ar S ty l e C har t E dito r $ $ . $ : !
194
, 6 % . $
.2
+ 3- .. # 6 ? ..
) 1 = .. ) 1 = E # 6 3
= 9 3 , 6 A p p l y A l l 4 > 4 1 F 1 3-D effect 3
: " ) 1 3
Establishment Sales by Years for Period 1990-1994 70
Value SALES
60
50 40
1990
1991
1992
1993
1994
YEAR
Iraqi Dinars (Thousands)
: 6 =
H @ ; 2 3 . $ C E @ A Dep th ; 2 3
. . $ C E
: % . ?1 K 0 :B ar Label S ty l e 9 3 3 .
F o r m at B ar Label S ty l e % . $
195
2 3 .A ? 3
.3
. . C " 3 # ! A p p l y
:
A l l 4 > 4 1 F 1 F r am ed
:
4 2 ..
Establishment Sales by Years for Period 1990-1994 70 65
Value SALES
60
60
50
50
40
1990
52
1991
55
1992
1993
1994
YEAR
Iraqi Dinars (Thousands) " .&
.&
: %6 =
C har t E dito r $ $ . $ C har t .. " .& 4 &
.
C har t E dito r $ $ . $ C har t .. " " .& 4 &
.;
. , = ) 4 & O u ter F r am e
S cal e A xis
. , = ) 4 & I n n er F r am e
1 ! % 3&
: " % 3& % .
C har t E dito r $ $ .. " (…J40، 50، 60) 3 C " 3 : " S cal e A xis !
196
, 6
.4
, " 1 2 ; 4 & ) . 4 A (
: 7
3:Dis p l ay A xis Lin e
. (I n n er F r am e C har t 1 " .& 4 A
.a
. ( V al u e S al es ) 3 ?2 :Titl e Ju s tificatio n
.b
. % :Maj o r div is io n s
.d
. ( G
J . ) > N :S cal e . % :Min o r div is io n s
≥ Maio r I n cr em en t Min o r I n cr em en t <" 3 1 :I n cr em en t . 1 $ . . (
. Tick Mar k s (
. (…J40، 50، 60) % 3 4 A (
3:G r id
) :Tick s
3 :Dis p l ay Label s
.c
.e .f
.g
.h .i
: 4 2 .. C " 3 % ) 0 / A . C en ter .
(V al u e S al es + ) 3 ?@
% = 3 , 6 A ? 10 <- 1 5 Min o r I n cr em en t % 1 # )
.Tick Mar k s
. % C G r id Lin es 1 $ . . @ A 3 1 D " 3 # ! ) ; S cal e A xis !
E
: ( 4 = %= ) 1
197
• • •
: O K 4 ) 1 " , 6 .. 5 2 ..
Establishment Sales by Years for Period 1990-1994
Value SALES
70 65
60
60
50
50
40
1990
52
1991
55
1992
1993
1994
YEAR Iraqi Dinars (Thousands)
Axis Title
Axis Label
: % ) 0 1 D = Label s !
, 6 4 3 : Label s
; 3 ) $ ) ; 3 : Decim al Pl aces
-
3 3 # 1 C H @ 4 : Leadin g C har acter
-
3 3 # , C H @ 4 : Tr ail in g C har acter
-
9 C o m m a 9 4 ) # ! 0 1 1000 3 4 (
-
. 70. 0J 60. 0J 50. 0J 40. 0: " ) (
) + $ )
. D70 J D6 0 J D50 J D40 : " ) , 6 D 2 ) 4 @ A . % 70J6 0 % J 5 0 %J 4 0 %: " ) , 6 %
= 3 @ A
) :10 0 0 S S ep ar ato r
. (Per io d
.J
3 1 .. , 6 . O r igin Lin e # ! . : B ar O r igin Lin e .K
. H # ! . 2 C " 3 < 2 # 9 3 7 1 9 2
B ar O r igin Lin e 2 A. D H . 2 # 2 2 # 9 3
( ) 1 = E 4 A ) 1 ) 4 2 .. " S cal e A xis !
57 +
: .. C " 3 # !
198
H
6 2 ..
Establishment Sales by Years
Value SALES
70
for Period 1990-1994 65
60
60 52
50
50
40
1990
1991
1992
1993
1994
YEAR
Iraqi Dinars (Thousands)
. 57 . 3 O r igin Lin e .
. 7
" # 1 F - @ A ( !
) : Dis p l ay Der iv ed A xis
Dis p l ay Der iv ed A xis $ E 1 K H " > D " !
: " Der iv ed A xis !
, 6 Der iv ed A xis 4 S cal e A xis
Der iv ed A xis # 1 S cal e A xis " ! 9 # # ) R atio Match
: " ; F = 3 ! Defin itio n 2 E 1 2 .. " S cal e A xis Der iv ed A xis U n its E q u al U n its 1 2 0
V al u e E q u al : .. C " 3 # !
199
.L
0
V al u e
O K 4 C o n tin u e 4 3
7 2 ..
Establishment Sales by Years 70
for Period 1990-1994
140 65
Value SALES
60
60
50
50
40
120 110
55
52
130
100 90
1990
1991
1992
1993
1994
80
YEAR
Iraqi Dinars (Thousands)
C " 3 2 # 6 = . L @ (
1 $ K Label s ) 0 @ 2
. Der iv ed A xis $ C " 3 H ) @ , " 1 " !
" ! # C " 3 ( ) 0 " 2 1 L Match
70 # 1 " ! C " 3 50 # ) . ?2 > 0 , 6 7 1 $
: " Der iv ed A xis ! S cal e A xis
R atio
1
Match
Defin itio n 2 ; 1 .. " $ C " 3
U n its E q u al
Der iv ed A xis
V al u e E q u al
50
: .. C " 3 # !
1
U n its
70
V al u e
O K 4 C o n tin u e 4 3
8 2 ..
Establishment Sales by Years 70
for Period 1990-1994
90 65
Value SALES
60
60
50
40
1990
55
52
50
1991
1992
70
1993
1994
YEAR
Iraqi Dinars (Thousands)
. # $ % …
2 0 0
8 0
80
! 6 0 7 0
! 50
60
C atego r y A xis 1 ! % 3& .5
S PS S
!
> 4 1 . . 1 1 ! % 3&
, 6 C har t E dito r $ $ .. " 3 V iew er
: ( <= 1 2 .. " )
: % ) 0 1 7
4 A , " 1 2 ; 4 & ) Dis p l ay A xis Lin e 4 A ( ) 1 A xis
3
•
Titl e # . ) # " 6 1 3
•
Titl e j u s tificatio n ) ?2
•
. (I n n er F r am e C har t 1 " .& .
3 (
. 1 $ . . % 4 A , 6 A
3 D Label s !
, 6 Label s 4 3
) ? 2 = 4 1 J 9 ) J , / 4 , )
• •
S tagger ed J Diago n al J V er tical J H o r iz o n tal : % 7 O r ien tatio n : " .. , 6 1 .. " 3 (
) Diago n al ) .
9 2 ..
Establishment Sales by Years
Value SALES
70
for Period 1990-1994
60 50 40
19
19
19
19
19
94
93
92
91
90
YEAR
Iraqi Dinars (Thousands)
, 1 ) K 1 $ <1 . F , 1 " . ) (
3 + @
. F V er tical S tagger ed 9 0 -
2 0 1
> ) 1 .$ C 9 3 .. # + ;" : S w ap ; " 2 3 <= % . $
A xis ;" 2 .6
F o r m at S w ap A xis
. $
: " , 6 D E 1 2 .. 10 2 ..
Establishment Sales by Years for Period 1990-1994 1990 1991 1992 YEAR
1993 1994 40
50
60
70
Value SALES
Iraqi Dinars (Thousands)
:
$ $ 3) .. 3 + S iz e D F o n t . N
S PS S
. $ F o r m at Text ) 1 (C har t E dito r .
S PS S C har t $ $ C # " .. 1 ) " 1 1 , 6 3 F o n t 2 > 4 1 ; " . R
) 1
E dito r
. ....A r abic Tr an s p ar en t A n dal u s A r ial (A r abic) . N
.
.;
C har t $ $ 3) .. .$ 1 .$ I / = & .
.%
$ $ . $ C har t Legen d 1 Legen d Q @ A " @ A
.7
.. " " .& 1 # ) # 1 9 3 1 % 1
.B
S PS S
.
. $ F o r m at
. Legen d !
F il l Patter n
(E dito r
Dis p l ay C har t Legen d $ E C har t E dito r
. $ C har t B ar S p acin g 1 C l u s ter 2 ) 1 K I n n er F r am e : # $ %
. . 1 .$ (
2 0 2
) 1 D 1
.. C " 3 0 " % " 3 0
L @
: Chart Template (213)
" " C " 3 % " ) > 0 0 ;" . (
) 1 , D " $ E C
F % 1 3 K A ! . " 3 1 ) F %
D 1 . 7 # .. C " 3 % % " ) @ Tem p l ate ; 2 # 3 & 1
J .P 1 9 3 3 J ) 1 = ) 0 " % " 3 @ 4 2 .. <= . M % C " 3 E + ) x C " 3 % " ) F > 0 1 . ( : % . ?1
" . (… 30 " ! )
(94S90 % " 80، 88، 110، 90، 77
C har t $ $ F il e S av e C har t Tem p l ate 1 ; 2 ! 1 4 .. 4
. cht ; s ct . - ; E 7 E dito r
G r ap hs
B ar . $
; L 0 F il e 4 C har t S p ecificatio n fr o m
$ E 1 2 tem p l ate
V al u es o f I n div idu al C as es
. F V al u es o f I n div idu al C as es !
y ear x % # (s im p l e)
: " V al u es o f I n div idu al C as es !
: x " .. C " 3 # !
; 7 cht
O k
Establishment Sales by Years 120
for Period 1990-1994
110
110
100
Value X
90 80
70
1990
77 1991
YEAR
Iraqi Dinars (Thousands)
2 0 3
90
88
80
1992
1993
1994
4 3
11 2 ..
L i n e B ar ( 3– 13)
: % . ?1 Lin e . . C B ar 9 3 1 2 .. Lin e !
, 6 G al l er y
. C har t E dito r $ $ ..
S im p l e . $
Lin e
" " S al es . 9 " @ .. - S im p l e ) C har ts . ( Mu l tip l e
, ) , @ ( )
: " Lin e C .. # R ep l ace
12 2 ..
Establishment Sales by Years 70
for Period 1990-1994
Value SALES
60
50
40 1990
1991
1992
1993
1994
YEAR
Iraqi Dinars (Thousands)
% . $
: % . ?1 1 . C " 3 Mar k er s
F o r m at
: " I n ter p o l atio n !
%= ) (
I n ter p o l atio n
)
, 6 ( C har t E dito r $ $ .. 3)
A p p l y 4 F $ E Dis p l ay Mar k er s C heck B o x ! ?1
: # $ .. C %= ) H @ A l l
2 0 4
13 2 ..
Establishment Sales by Years 70
for Period 1990-1994
Value SALES
60
50
40 1990
1991
1992
1993
1994
YEAR
Iraqi Dinars (Thousands)
!
: " ?1 = ) # $
. $ E %= ) C har t E dito r $ $ .. , 6
F o r m at
Mar k er s
. , = ) N
: Mar k er s
: " = ) A p p l y 4
14 2 ..
Establishment Sales by Years for Period 1990-1994
70
Value SALES
60
50
40
1990
1991
1992
1993
1994
YEAR
.A
2 0 5
Iraqi Dinars (Thousands)
p p ly A ll
! " # ( ) :
P i e B ar ( 4 – 13 )
: % . ?1 Pie 1 9 C B ar 9 3 1 2 .. Pie C har ts !
. C har t E dito r $ $ ..
, 6 G al l er y Pie . $
: " Pie C .. # R ep l ace S im p l e
15 2 ..
Establishment Sales by Years for Period 1990-1994
1990
1994
1991 1993 1992
Iraqi Dinars (Thousands)
$ $ ( C "3 # !
: % . ?1 <= 1994 R
9 ?. # ! 0
) . . E ) 1 F 1994 1 R
?.
5
F o r m at E xp l o de S l ice . $
5
. C har t E dito r : ..
Establishment Sales
16 2 ..
by Years for Period 1990-1994 1994
1990
1991 1993 1992
Iraqi Dinars (Thousands)
> 4 1 ? . D " 3 C # ! 0 ?. 9 3 .
2 0 6
F o r m at E xp l o de s l ice
: % . ?1 I n s ide S l ice ?. # # # " 1 (
, 6 ( C har t E dito r .. E ) 1 ) C har t
O p tio n s
)
5
: " D 1 + Pie O p tio n s !
. ?. # Text 1 (
) Label s Per cen ts $ 6 -
: " ; + Label F o r m at !
, 6 F o r m at 4
in s ide O u ts ide Ju s tified) Text V al u e 2 1 (
: 7
3 ?2 # : Po s itio n
;G I n s ide 2 . ( n u m ber s in s ide Texts O u ts ide . . ) ?. 1 .1 . . (
J B es t fitJ O u ts ideJ
. ?. # 1 (
3
) : C o n n ectin g Lin e fo r O u ts ide Label s
. > , . . # ) : A r r o w head o n Lin e
. " ) # .A (
) : Dis p l ay F r am e A r o u n d
.. " $ ) ; 3 1000 3 4 3I # ! @ & : V al u es : .. C " 3 # !
2 0 7
O k 4 C o n tin u e 4 3
5
17 $ % & & '
Establishment Sales by Years for Period 1990-1994 1994 23.0% 1993 21.3%
1990 17.7% 1991 1992
18.4%
19.5%
Iraqi Dinars (Thousands)
y ear 1998 1999 2 0 0 0 2 0 0 1 2 0 0 2
E xp o r ts 190 2 2 0 2 19 2 4 5 2 5 0
. 2002S8199 % " " 1 % % ! I m p o ts 180 2 0 0 2 15 2 30 2 4 4
: 2 #
# #
: " ;" .
. C l u s ter ed B ar s 3. ( .$ - ) 9 3 .. 3
. S tack ed B ar s 9 3 .. 3
D B ar C har t ! !
2 0 8
: % . ?1 3. 9 3 3
, 6 G r ap h
B ar . $
5
.1
.2
, 6 Defin e 4 V al u es o f I n div idu al C as es / C l u s ter ed : " D 1 + C l u s ter ed B ar / V al u es o f I n div idu al C as es
.1
: .. C " 3 # ! 260
O k 4 3
18 2 ..
5
240
220
200
Value
180 EXPORTS 160
# 1 S tack ed
2 0 9
IMPORTS 1998
1999
2000
2001
2002
YEAR
7 2 2 9 . 3 , 0 1 % . ?1 S tack ed B ar .. 0 .2 : .. C " 3 # !
7 B ar C har ts !
C l u s ter ed
19 $ % & & ' 600
500
400
300
200
Value
100
IMPORTS
0
1998
1999
2000
2001
2002
EXPORTS
YEAR
< (
) E xp o r ts " " ( # 0 ) <- (
) I m p o r ts " " # ) (
0 1
.. K 0 .. 1998 4 A ;G K C @ & 1 (C " 3 )
+ S er ies Dis p l ay ed . $ C har t E dito r $ $ : !
2 10
, 6 " "
( < 1 ) (C " 3 )Dis p l ay E xp o r ts " " (. . # = ) O m it C , " ( @ ) # = ) Dis p l ay C D "
C O m it E xp o r ts " " N &
5
4
4
. Dis p l ay # = ; G 2 , 1
4 F (# 0 ) Dis p l ay
1998 )
. O m it H
: " ) 1 !
: .. (
5
, 6
) , 6 O K 4 3
20 2 ..
600
5
500
400
300
200
Value
100
/ , -
0
, . $
: & & ' (
2 11
EXPORTS
1999
2000
2001
2002
IMPORTS
YEAR
B ar + * " # ) * I m p o r ts Lin e & ' " # ) * E xp o r ts ( : B ar /Lin e/A r ea Dis p l ay ed Data
O K * E xp o r ts Lin e I m p o r ts B ar ' 0
2 1$% & & ' 260 250 240 230 220 210
Value
200
EXPORTS
190
1999
2000
2001
IMPORTS
2002
YEAR
:
C " 3 # ! # ) 1 . 1 B ar . . P ie Line . . C " 3 " !
: " B ar . . C " 3 " ! " 9 ! 1 % . . F
Line . . C " 3 # ! "
G r ap h
Line
Ar ea . . C " 3 # ! "
G r ap h
Ar ea
P ie . . C " 3 # ! "
G r ap h
P ie
(Su mmar ies o f Sep ar at e Var iabl es C " 3 ) 3 #
Dat a E d it o r $ $ % 1 % " 2 g x2 x1 # # x1 10 0 20 0 30 0 4 0 0 50 0
x2 10 20 30 4 0 50
: " SP SS 5 1
g a b a b b
: " ; " .
. x2 x1 . B ar . . 3 .1
. x2 x1 " ( b a) % . Cl u st er ed B ar 3 . 2 . . 3 .2
: % . ? 1 x2 x1 . B ar . . 0 .1
D B ar Ch ar t s !
!
2 12
, 6 G r ap h
B ar
. $
5
, 6 ! Def ine 4 3
5
. Su mmar ies o f Sep ar at e Var iabl es / Simp l e
: " D 1
+ Def ine Simp l e B ar : Su mmar ies o f Sep ar at e Var iabl es
- . 7 x2 x1 # . # 9 3 6 =
% $ ' L + Ch ange Su mmar y 4 1 . N @ - . M ed ian, M o d e, No .o f Cases , M in. Val u e, M ax. Val u e … # M : B C "3 # ! O K
400
300
4 3
5
22 2 . .
300
200
Mean
100
0
30
X1
X2
.
x2 ) N 0 300 + " 1 .
x1 ) N 0
. 30 + " 1
? 1 x2 x1 " ( b a) % . Cl u st er ed B ar 3 . . . 0 .2 D B ar Ch ar t s ! : " D 1
213
!
, 6 G r ap h
: % .
B ar
. $
. Su mmar ies o f Sep ar at e Var iabl es / Cl u st er ed
, 6 ! Def ine 4 3
+ Def ine Cl u st er ed B ar : Su mmar ies o f Sep ar at e Var iabl es
5
: . . C "3 # ! O k
4 3
23 2 . .
5
400
367 300
200
200
Mean
100
0
20
a
37
b
X1 X2
G
.
(
Su mmar ies o f G r o u p s o f Cases ' ) * ) : 4
gend er 3 d eg 2 1 2 * sal ar y 1 " " d eg gend er sal ar y F ir st M al e 9 0 F ir st F emal e 70 T h ir d M al e 56 Seco nd M al e 65 F ir st M al e 8 5 Seco nd F emal e 60 Seco nd M al e 69 T h ir d M al e 57 T h ir d F emal e 50 F ir st F emal e 75 Seco nd F emal e 62 T h ir d F emal e 51 F ir st M al e 8 5
214
: " ; " .
. 7 & 0 ; . # B ar s 1 9 3 1 . . 3
.1
# ; 7 & # ; . # B ar s 1 9 3 1 . . 3
.2
. 0 6
D B ar Ch ar t s !
Def ine Simp l e B ar : !
: % . ? 1 # ; " . 0
, 6 G r ap h s B ar
. $
5
Def ine 4 3
5
. Su mmar ies f o r G r o u p o f Cases/Simp l e
, 6 F = 3 !
: " ; + Su mmar ies f o r G r o u p o f Cases
: & & ' ) * " - 74 72
72
70 68
Mean SALARY
66 64 62 61
60
Female GENDER
215
.1
Male
O K *
24 $ % & & '
5
D B ar Ch ar t s !
: % . ? 1
, 6 G r ap h s B ar
; " . 0 . $
.2
5
C " 3 0 6
# 7 Su mmar ies f o r G r o u p o f Cases/Cl u st er ed
. Cl u st er s 7 ; . ; . 3 0 6 # # 1
!
, 6 F = 3 !
Def ine 4 3
: " ; + Def ine Cl u st er ed B ar : Su mmar ies f o r G r o u p o f Cases
: & & ' ) * " -
O K * 5 25 $ % & & '
90 87 80
73
70
67
Mean SALARY
60
61 57
50
51
40
First DEG
216
5
Second
Third
GENDER Female Male
- SP SS 5 1 % . . , 1 ? , 9 4 6 =
# =
B 7 % 1 " ! & ) E XCE L # M % 1 . % . .
, " ! ) < 1 , " ) % 0 <= 1 % . ! & % $ '
% 1 - % < 1 % 1 A ! % 1 ; 4 = % 2
. ! &
B Ro w Dat a % 1 ( % 1 # P 1
Histogram ( 5 – 13 )
) # ) p ie Line B ar 1 % . .
G C " 3 G r o u p ed Dat a 1 1 % 1 (
) # ) +
? 4 # C % 1 H ! 1 5 1 7 SP SS 5 1 C U ngr o u p ed , ! 1
% 3 A 7 # , + B < " F r eq u ency T abl e +
. # (… J 0 # . J % 0 3 ) . . 5 #
> 0 ) Dat a E d it o r $ $ < 1 # + t al l " + B ; " .
. (? 1 # ! 0 (1S4) 1 " ? 1 #
H ist o gr am !
217
, 6 G r ap h
: % . ? 1 + B H ist o gr am . $ 5 : " D 1
+
: 5 6 (
* $
O K *
26 $ % & & '
5
10
8
6
4
2
Std. Dev = 17.17 Mean = 68.2
0
N = 56.00 30.0
35.0
TALL
40.0
45.0
50.0
55.0
60.0
65.0
70.0
75.0
80.0
85.0
90.0
95.0
100.0
Cl asses 7 8 2 " . 1 ; < ) * M id p o int s 7 8 2 " $ 9 : : 7 & ' > . ? @ @ 2 . 1 0 , . I nt er v al Wid t h 8 2 " & = 7 8 2 * = * < . Ch ar t E d it o r # # ) " H ist o gr am & & ' : / - ! < *
) *
218
!
, 6 F 3 Def ine 4 4 0 I nt er v al s Cu st o m 4 : " D 1
2 1 30 @ ) 2 # 2 " ) I nt er v al
+ Def ine Cu st o m I nt er v al s
wid t h
10 1 0 # .
: 2 = ) ; + 7 + % 0 3 E D " 3 100 @ ) Range 70 No. of Classes = = =7 Class (Interval) Width 10
Label s 4 I nt er v al axis ! : " D 1
C " 3 % 0 (
3 ; G
C N " co nt inu e 4
+ Label s !
, 6 !
: % " ) 1 2 7
T yp e M id p o int <- 1 Range
.1
. Decimal P l aces % 0 " " ) " 0 ! 1 $ ) ; 3
.2
. % 0 4 <- 1
. , 1 % 0 K 1 $ - Diago nal O r ient at io n
. . (
) O K
4 I nt er v al axis !
.3
C N " Co nt inu e 4 27 2 . .
219
•
:
16 14 12 10 8 6 4
Std. Dev = 17.17 Mean = 68
2
N = 56.00
0
90
80
-1
-9
00
0
0
0
0
0
0
-8
-7
-6
-5
-4
TALL
70
60
50
40
30
> .& ) (
No r mal Ch ar t E d it o r $ $ . . 3 H ist o gr am !
Ch ar t
O p t io ns
Disp l ay No r mal Cu r v e $ E K Disp l ay cu r v e . # ) 1 ! ; 3
B ox P l ot ( 6 – 13)
? ) M ed ian .
# % $ 3 ? 4 H !
. . # )
. ( . . % # # ! 0 4 1– 6 1
Dat a E d it o r $ $ C % " % 3 @ # x 30 20 31 35 10 0 8 0 79 55 50 60 9 5 4 5 39
y 4 7 66 77 9 0 55 62 8 0 9 9 4 3 8 7 9 2 70 4 0
cat a a a a a a b b b b b b b
z 20 60 50 8 0 10 0 70 8 9 35 65 4 0 55 69 4 0
g a b a b b a b a b a b b a
: " SP SS 5 1
gend er f f m m m m m f f f f m m . x " B o x P l o t s . . ; " .
.1
. y x " B o x p l o t . .
.2
. g (b a) z 0 B o x P l o t . .
.4
. cat b a 0 ; y x " B o x P l o t . .
220
: 6 #
.3
0 # < " 3 g ( b a ) z 0 B o x P l o t . .
. f 7 O M m " A 1 @ .
:
.
.5
: " ? 1 # ; " . 0 .1
B o xp l o t / - ! G r ap h s B o x p l o t . $
- 7 ) Simp l e ? su mmar ies o f Sep ar at e Var iabl es 6 Def ine Simp l e bo xp l o t : !
. ( x " % ) Cl u st er ed
, 6 F = 3 !
: " D 1
Def ine 4 3
+ Su mmar ies o f Sep ar at e Var iabl es
Label Cases by 2 # A B o xes Rep r esent # A
3 (. . ) , 6 ) 9 $ . " Label 3 1 G 3 . , ) 9 $ . , @
? 2 # ) # A
: . . C "3 # ! O K
221
4 3
28 $ % & & ' 120
80
M a x . = 1 0 0
Q 3 = 7 9 IQR=Q3-Q1 =4 4
100
60
40
M e d ia n = 5 0
20
Q 1 = 3 5 M in . = 2 0
0 N=
D 1
+ B o xp l o t !
13
X
, 6 G r ap h s
: " ? 1 ; " . 0 .2
B o x p l o t . $
: "
Def ine Simp l e B o x p l o t : Su mmar ies o f !
, 6 Def ine 4 3
: D 1
: . . (
222
+ Sep ar at e Var iabl es )O K
4 3
29 2 . . 120
100
80
60
40
20 0
N=
13
13
X
Y
, ' $ 8 , ,
G r ap h s
Su mmar ies o f Sep ar at e Var iabl es !
: " D 1
: 7 & ' > . : 1 & @ 2 .3
, 6 !
D B o x P l o t !
Def ined
, 6 B o xp l o t
4 3 Cl u st er ed ?
+ Def ine Cl u st er ed B o x P l o t : Su mmar ies o f Sep ar at e Var iabl es
Cat ego r y Axis # 2 @ ; B o x Rep r esent 6 -
. C " 3 D # +
: . . (
)O K
4 3
30 $ % & & '
120 100 80 60 40 20
X
0
N=
6
6 a
223
CAT
7
7 b
Y
!
D B o x P l o t ! Def ined
: % . ? 1 ? 1 ; " . 0
, 6 G r ap h s B o xp l o t
.4
4 3 Simp l e ? Su mmar ies f o r G r o u p o f Cases
Def ine Simp l e B o x P l o t : Su mmar ies f o r G r o u p o f !
, 6
: " D 1
: . . (
)O K
+ Cases
4 3
31 $ % & & '
120 100 80 60 40
Z
20 0
N=
G
!
D B o x P l o t ! Def ined
6
7
a
b
: % . ? 1 > ; " . 0 .5
, 6 G r ap h s
B o xp l o t
4 3 Cl u st er ed ? Su mmar ies f o r G r o u p o f Cases
Def ine Cl u st er ed B o x P l o t : Su mmar ies f o r G r o u p o f !
, 6
: D 1 +
224
: & & ' (
O K *
32 $ % & & '
120 100 80 60 40
GENDER
Z
20
f
0
N=
3
3 a
3
4
m
b
G
S c atte rp l ot ( 7 13)
9 . 3 1 1 2 = ) # % . . N # )
. $ - # $ N ) 1 @
SP SS 5 1 Dat a E d it o r 2 % " %
225
: 7 #
3 @ #
: "
y
79 74 10 4 8 7 9 5 10 9 10 2 72 9 3 115 8 3 113 10 9
x1 26 29 56 31 52 55 71 31 54 4 7 4 0 66 68
x2 6 15 8 8 6 9 17 22 18 4 23 9 8 : $ -
x3 mar k er 60 a 52 a 20 a 4 7 a 33 a 22 a 6 b 4 4 b 22 b 26 b 34 b 12 b 12 b # $ ) 1 N
l abel c1 c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 c13 3 0 L @ " #
Simp l e . 1 $ - # $
D + ) # $ " # . 1 2 = ) # )
.1
1 2 = ) " . 1 $ - # $ 3 J C " 3 ) # $ . # % A
: Scat t er p l o t !
: % . ? 1
, 6 G r ap h s Scat t er . $
x1 y
Simp l e / - ! Def ine $ A . Simp l e ' A * / - : 9 . 5 @ scat t er p l o t
: 7
. $ - # $ # + F @ : Y Axis . $ - # $ # + F @ : X Axis
226
, 1 ! M ar k er = ) 1 # # D F @ : Set M ar k er by . $ - # $
D 7 $ - # $ . Label s ) D 2 # ) F @ : Label Cases by . , 0 A ) , 6 A & 1
3 & 1 + O p t io nal l abel Cases by Set M ar k er s by < " 3 : . . (
. , + # A
)O K
4 3
33 2 . .
120
110
100
90
MARKER
80
Y
b 70
20
30
40
50
60
70
80
a
X1
Label 2 " ) G C " 3 . . , 6 % - 3 6 -
: " ? 1 ) , 6 & J % - " )
!
227
. Ch ar t E d it o r $ $ C . . # > 4 1 . . , 6 Ch ar t
O p t io ns . $ Ch ar t E d it o r $ $ : " D 1
+ O p t io ns
•
•
: % = + Case Label s% - 3 (
3 6 Case Label s 7 . % - 3 4 & : o f f
Ch ar t $ $ , 1 R
) (
. % - 3 (
. H ) % - / 4 3 (
) :o n
) : As is
) . . . + 3 I < , 1 $ > # $
L 1 ! E d it o r
. ( 9 # 3 / , & ) .
. o n % - 3 (
3 ; G
1
: ; % - 3 ! 1 So u r ce o f Label s
) ) # # ) # # ) : I D Var iabl e . Simp l e Scat t er p l o t !
F " 2 Label
. % - ) 3 ) 2 # ) : Case Nu mber : " % - 3
(
) F = 3 !
O K
4 3
34 2 . .
•
120 c10
c12 c6
110
c13
c3
c7
100 c5 90
c9
c4 c11 c1
80
MARKER
Y
c2
b
c8
70
a 20
30
40
50
60
70
80
X1
Simp l e ! !
O p t io ns 4 1 9 $ 1 % - 3 (
3 : 1 6 =
Disp l ay Ch ar t Wit h Case Label s $ E Scat t er p l o t
. O p t io ns
) Sh o w Su bgr o u p s Scat t er p l o t : O p t io ns ! a 3 # ) 3 0 ? (
228
: 2 6 =
3 < $ ' ( Disp l ay O p t io ns
(
1 ? 1 b ? 1 ) F = 3 . . , # 0 "
. . . 9 = ) 1 3 (
% = ) 1 ( b
3 $ E 3 3 ( a 35 2 . .
120
c10
c12 c6
110
c13
c3 100
c5
90
c7
c9
c4 c11 c1
80
Y
c2 70
20
MARKER
c8
30
40
50
60
70
80
Total Population
X1
ˆ = B + B X C - . @ & : 3 6 = Y 1 3 1 Y 0 1 1 ( E(Y0 ) = B 0 + B1X 0 ) Y . % 9 5 9 ? # X1 ) !
: % . ? 1 1 . . "
, 6 Ch ar t O p t io ns (Ch ar t E d it o r $ $ ) . $ : " D 1
5
+ Scat t er p l o t O p t io ns
# $ . # . @ A ) + F it Line T o t al $ E 1 2 6 -
. M ar k er . b a 4 3 1 3 - 1 E + $ -
229
D 1
+ F it Line !
, 6 1 !
F it O p t io ns 3
: "
1 ) J ) 1 ) . Linear
9 ; G
Regr essio n 6 -
1 ( - C 4 M ! % ) 1 .
I nd iv id u al 3 ) Regr essio n P r ed ict io n Line M ean . " % 9 5
. ( Y0 = B 0 + B1X 0 + e0 " " 9 5 1 ( ) : (Case Label s 4 A ) 1 ) . . ( ) O K 4 co nt inu e 4 3 5 36 2 . .
120
+ 2 ) * <
& % 95
110
100
90
+ 2 ) <
& % 95
Y
80
70
20
30
40
50
60
70
MARKER Total Population 80
Rsq = 0.6648
X1
Scat t er p l o t : O p t io ns !
F it Line Su bgr o u p s $ E : 6 =
; F ( M ar k er # . ) . (
) 5 1 E
. < $ ' Disp l ay O p t io ns Sh o w Su bgr o u p s
230
O v er l ay $ # $
Y " $ # $ # # 2 C " 3 % 4 $ - . # # )
: % . ? 1 . . X3 X2 " K X1
D Scat t er p l o t !
: " D 1
, 6 G r ap h
+ O v er l ay Scat t er p l o t !
Scat t er
5
, 6 Def ine 4 3 O v er l ay
: ( X1 Y = ) Y-X P air s % B 4 # A . F - Y
. F - X1
. Y-X P air s C #
. X3 X2 # A . > 0 1
. % - 3 (
. F ) 1 % B 4 + > ) # ) : Swap P air ) Disp l ay Ch ar t wit h Case Label s O p t io ns 4
: . . (
) O v er l ay Scat t er p l o t !
120
c10
c5c9
c4 c1
80
c2
c12 c13
c6 c3
100
O K
4 3
37 2 . .
c7
c11
c8
60
40
0
c12 c13 0
c11
c9
c7
20
10
c3c6 20
c8 c4
c5
c10 30
40
X2
c2
X3 c1
50
60
Y 70
80
X1
• •
J C " 3 # X1 + ) C " 3 D " Y 7
231
.2
5
5
•
M at r ix $ - # $
M at r ix. . <=
. # # )
D Scat t er p l o t !
: " D 1
.3
: % . ? 1 X3 X2 X1 % "
, 6 G r ap h
Scat t er
+ Scat t er p l o t M at r ix !
5
, 6 M at r ix
C " 3 , A E @ 2 7 < Label mar k er # < " 3 : . . , 6 O K 4 3
.. .
38 2 . .
5
X1
X2
X3
$ $ C # > 4 1 . . Axis T it l es_ 3 @ &
Scat t er p l o t M at r ix !
, 6 Ch ar t
Axis . $ Ch ar t E d it o r
: " ! , 6 Disp l ay Axis T it l es $ E 1 7 Scal e Axes
232
E d it Sel ect ed
!
. . C "3 # ! O K
, 6 1 !
E d it 4 ) .
Co nt inu e 4 1 J u st if icat io n Cent er D Axis :
X1
X2
X2
X1
39 $ % & & '
X3
X3
X1
X2
X3
3-D ) 1 = $ - # $ .4
Y % " 3-D. . <=
. ) 1 = . . % = # ) 3-
233
D Scat t er p l o t !
, 6 G r ap h
: " D 1
: % . ? 1 X2 X1
Scat t er
+ 3-D Scat t er p l o t !
5
, 6 D
: . . (
)O K
4 3
5
40 $ % & & '
120 110 100
Y
90 80 70 80
70
60
50
X1
40
10
30
Ch ar t E d it o r $ $ % . $
X2
30
20
:1 6 =
1 ) 1 = . .
. . $ F o r mat 3D-Ro t at io n
: 2 6 =
Ch ar t O p t io ns 1 # $ @ C $ - # $ . . . @ A
F lo o r
D 3-D Scat t er p l o t O p t io ns !
, 6 Ch ar t E d it o r $ $ 2 . $
: . . C "3 # ! O K
4 1 Sp ik es
41 2 . .
120 110 100
Y
90 80 70 80
70
60
50
X1
40
: 3-D Scat t er p l o t O p t io ns !
30
10
X2
20
30
Sp ik es D < " 3
. Cent r o id # $ . 4 C $ - # $ . . # . : Cent r o id
. O r igin # ! . C $ - # $ . . # . : O r igin
234
Data Exchange :% 0 " N ? # ) SP SS 5 1 0 " ` ! 1 E % 1 % 0 " . ASCI I R
. E xcel Lo t u s 1-2-3 1 1 !
5
!
5
. d B ase % 0 "
% 0 " M N , T ab-d el imit ed % 0 "
. M # $ 6 . 1 SP SS % 0 " . SYST AT % 0 "
. M % 1 . C % 0 " ( 4 ) ! M % 1 . % 0 " (L ) 7
5
5
5
Importing Data files ( 1 14 )
5 1 R
(E XCE L 9 7 5 H " ) : 1 #
$ 3 2 + mer ge " 4 T est H "
: # $ , 6 E xcel 9 7
. SP SS 5 1 C E xcel ! , 6 F il e O p en
235
T est H " ; " .
: % . ? 1 K 0
Dat a SP SS 5 1 . $
: " ; + O p en !
5
F il es o f T yp e J F il e Name T est H " 1 6 -
% 0 " # % 0 " 9 3 N L & 1 D 7 xl s . - % E xcel % 0 "
% 0 " ( SAV . - % Wind o ws 6 " SP SS 5 1 % 1 % 0 " ) SP SS(* .SAV) d B ase(* .d bf ) % 0 " Lo t u s(* .W* ) % 0 " SP SS/P C+ (* .SYS) DO S 6 " SP SS
. % 0 " G T ext (* .t xt ) % 0 "
: !
, 6 o p en 4 3
5
: 7
# H ! % / 9 / : Read Var iabl e Names F r o m T h e F ir st Ro w o f d at a . E xcel H "
. SP SS 5 1 C , " % 1 + 2
: Wo r k sh eet
. SP SS 5 1 C , " % 1 ) M : Range
Dat a E d it o r $ $ % 1 , 6 SP SS C E xcel H " # O K
4 3
5
: "
. SAV . - SP SS H " 1 H " 4
:
236
O p ening E xcel !
Range # % 1 ) Range 3
.1
: 5 , 6 (A1:A3 <= ) Dat a So u r ce
Wo r k sh eet Sh eet 1 <- 1 Sh eet 2 <= H " # 3 2 +
+ 2
F 9 % 1 - O p ening E xcel Dat a So u r ce !
.2
. 2
F % 1 Range
# Read Var iabl e Names F r o m T h e F ir st Ro w o f d at a $ E 3 3
.3
SP SS H " # 2 # E H @ H E xcel H " % / E 1 . , 3 <- 1 @ % / @ A
D H # E E xcel H " - > 0 1 3
.4
4 D E xcel 5 1 # SP SS 5 1 C H " 3 U niq u e
) # - @ A 4 8 - ? . 2 8 3 3 4 Ch ar act er s . SP SS 5 1 C H " 3 Label "
E xcel 5 1 , " ; " . % 1 # " 6 1 . 1 E xcel H " % 1 . $ E d it P ast e
SP SS 5 1 C # - E d it Co p y
.5
/ 6 = ; SP SS 5 1 C % 1 # Dat a View $ $
4 % 2 6 =
, 3 <- 1 @ / , 6 %
N F ; Nu mer ic + ) N SP SS % @ - N
. Z " 3 4 A # 1 2 Dat a E d it o r $ $ 4 % " St r ing ( T ext F il es R
5 1 M S-DO S E d it o r R
!
!
% 0 " ) : 2 #
5 ) . 3 , A % 1 + H "
: " % 1 # ! 0 " Sp aces % G 0 % 2 Var .t xt E 1 4 M S-DO S
237
x1 12 16 29
x2 x3 30 33 4 5 60 64 8 8
O p en F il e !
: % . ? 1 SP SS 5 1 C F = 3 H "
, 6 F il e Read T ext Dat a
F . $ F il e
. F = 3 !
T ext I mp o r t wizar d
238
O p en
. $ : " D 1
5
+
Dat a 1 9 . F 4
F il es o f t yp e # T ext H " N ;
!
, 6 F = 3 !
O p en 4 3
5
: " (st ep 1o f 6)
: 2 $ % + & ' ) " 0 $
239
Next *
5
# ) + Del imit ed $ H o w ar e yo u r Var iabl es ar r anged ? #
. (Z .… J e J . 9 4 J 9 4 ) ) N # ! , 1 # ! 0 % "
. yes $ Ar e Var iabl es Names incl u d ed at t h e t o p o f yo u r f il e?
#
: " 3 9 . C # - Next 4 3
5
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5
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5
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5
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L 0 Anal yze
Descr ip t iv e St at ist ics
5
F r eq u encies
. F r eq u encies
$ E ` Var iabl e(s) 2 C Y X # F r eq u encies !
5
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5
. St at ist ics !
L 0 St at ist ics 4 . Disp l ay F r eq u ency T abl es
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4
5
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5
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7 J SP S . - 1 (t h r ee j o bs <= )H "
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Ru n Al l ' * 5 R e g r e s s io n
Model Summaryb M o d e l 1
R .900a
RS q u a re .8 10
a . P r e d ic to r s : ( C o n s ta n t) , X b . D e p e n d e n t V a r ia b le : Y
A d ju s te d RS q u a re .7 8 7
S td .E rro r o f th e E s tim a te 8 .8 2
D u r b in - W a ts o n 1.8 8 5
ANOVAb M o d e l 1
S u m o f S q u a re s 2661.050 622.950 3 284 .000
R e g r e s s io n R e s id u a l T o ta l
d f
M e a n S q u a re 2661.050 7 7 .869
1 8 9
a . P r e d ic to r s : ( C o n s ta n t) , X b . D e p e n d e n t V a r ia b le : Y
F 3 4 .17 4
S ig . .000a
Coefficientsa
M o d e l 1
U n s ta n d a r d i z e d C o e f f i c i e n ts B S td . E r r o r 85.044 9 .9 7 0 1.140 .19 5
( C o n s ta n t) X
a . D e p e n d e n tV a r ia b le : Y
G ra p h 180 170 160 150 140 130
Y
120 110
20
30
40
50
60
70
X
F r e q u e n c ie s N S u m
25 1
V a lid M is s in g
Statistics X
10 0 4 9 1
Y
10 0 14 10
S ta n d a r d i z e d C o e ffic ie n ts Be ta .9 00
t 8.53 0 5.846
S ig . .000 .000
D 1 ! # " 6 1 Regr essio n 0 <= / 4 0
5
3 0 0 # 1 F G 3 0 - D < " 3 Ru n Sel ect io n
Ru n
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Cu r r ent ) G r ap h C " 3 $ ' ? 2
1 . . (
3 % . $
5 1 . . (
3 Ru n
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5
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: % . ; K E
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. Y1 1 Y # X1 1 X # # 1 P 1 H " L . Ru n 5 1 $
25 2
5
5
5
5
Multiple Response Analysis
) % 0 3 4 0 " 5 1 <= D # # ' 3 ; 1 A
3 ; # A . 9 7 = % 0 . 9 D P 1 E (/ + J .
% E F 9 0 !
# K E D 9 H !
: # " 1 " K 9 ) % 1 - # " . 3 F r eq u encies
C " 3 # ! D : M u l t ip l e r esp o nse F r eq u encies 1 - 9 ) % ; "
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C " 3 # ! D : M u l t ip l e Resp o nse Cr o sst abs 1 - 9 ) ? . # ; "
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Multiple response Frequencies ( 1 – 16 ) 1
J , J # 1 1 ) " H ! 9
. # @ 0 ) 1
# " @ 0 R
$ - 3 ) 0 !
# % ) (
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: 1 " 1 - D ( H ! 0 !
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0 !
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# R
!
E
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d it o r $ $ % 1 ; . 1 . 1 # . 0 ! al ir aq q ad issya t h o wr a 1 1 0 0 0 0 1 0 0 0 1 1 1 0 0 0 1 1 1 0 0 : % . ? 1 0 ! # " 1 % &
Anal yze M u l t ip l e Resp o nse Def ine Dat a E d it o r $ $ . $ : " D 1
25 3
set s + Def ine M u l t ip l e Resp o nse Set s ! , 6
: F = 3 , 6 !
; % . 1 2 2
Var iabl es in set C , " Set d ef init io n % . Dich o t o mies Co u nt ed v al u e ) 1 ( ) ) 1
•
.
Name C " 3 4 ) 1 9 ) 1 - 3 / . 3 A
• •
M u l t r esp o nse set s C 3 @ & Ad d 4
•
. ( 3 " Label 3 / . 3 A ) p ap er
9 0 = p ap er E 1 9 ) 1 - 3 4 ! !
, 6
Anal yze M u l t ip l e Resp o nse : D 1
Cl o se 4 3
. ) 1 ,
F r eq u encies
: . 1 + # C " 3 # ! F = 3 !
25 4
+ M u l t ip l e Resp o nse F r eq u encies
. T abl es f o r C $ p ap er 1 - 3 # 1 2 7
M u ltip le R e s p o n s e G r o u p $ P E P E R
O K
4 3
( V a l u e D i c h o t o m y N a m e B A J A A L Q A T H
B Y M H I R D I O W
T o t a l 0
t a b u l a t e d
l a b e l
L O N O R Y A A Q S S Y A R A
o f
P c t
o f R e s p o n s e s
5
2
c a s e s ;
1 )
C o u n t 2
r e s p o n s e s
m i s s i n g
P c t
=
3
1
4
- - - - - - 1 6 7
v a l i d
H ) Z ... J amh o r ya B abyl o n
- 1
1
1
3 1 . 3 2 . 5 2 5. 0 8 . 8 2 . 5 - - 0 0 . 0
C a s e s 7 1 2 8 . 57 42 . 2 8 . - - - 2 2 8
. 4
6 . 1 9 6 . 6
c a s e s
:
Dat a E d it o r $ $ , 6 %
E 1 H ) $ p ap er E 1 , 3 E l ement ar y Var iabl es % 1 . % 9 3 @ M u l t ip l e r esp o nse Set 9 ) % 1 - 3
, 6 Label s % F 3 E # " % " 3
# % , 6 % / E # % / <- 1 + #
.1
.2
. % " 3 . )
; D ; " 1 . : Multiple C a teg or y Method !
( ; M " @ 0 H ! 3 1 + ) # ' C " 3 % 1 & 3 1 ) - , % ) > 0 # 1 C " 3 H !
= ) (
.2
0
: % , # 2 7 X3 X2 X1 1 = B abyl o n , 2 = J amh o r ya , 3 = Al ir aq , 4 = Q ad issya , 5 = T h o wr a E X1 ) # 1 1 H ! = # @ 0 ; A <= # 1 1 0 !
# @ 0 ; 4 D X3 3 D X2 1
9 0 2 D X3 X2 " 2 X1 " 1 R
! E . ,
Dat a E d it o r $ $ X3 X2 X1 % ; E 1 # " 1 1 . M issing Val u e X1 X2 1 3 1 2. 3. . 1 4 2 3. 1 4 1 3. < 1 , 1 $
5 5 % . ? 1 ( # + ) 0 !
Analyze M u lt i p le R es p o ns e
25 5
: "
X3 4
# " 1 % &
: 0 % 9 ) % ; "
D ef i ne s et s Dat a E d it o r $ $ . $
: " D 1
+ < 0
Def ine M u l t ip l e Resp o nse Set s !
C , " Set d ef init io n X3 X2 X1 = %
•
C 1 H ! % ) Var iabl es Ar e Co d ed As Cat ego r ies
•
Name C " 3 4 ) 1 9 ) 1 - 3 / . 3 A
•
M u l t r esp o nse set s C 3 @ & Ad d 4
•
, 6
. Var iabl es in set . ( Range 1 t h r o u gh 5 ) 5
. ( 3 " Label 3 / . 3 A ) p ap er
9 0 = p ap er E 1 9 ) 1 - 3 4 ! !
, 6
Cl o se 4 3
. ) 1 ,
F r eq u encies
Anal yze M u l t ip l e Resp o nse
C $ p ap er 1 - 3 # 1 2 7 M u l t ip l e Resp o nse F r eq u encies : . 1 + # C " 3 # ! !
G r o u p
l a b e l
C o d e 1
P c t C o u n t 5
2 3 4 5
0
4 3
$ P A P E R
C a t e g o r y
3
T o t a l
O K
. T abl es f o r
r e s p o n s e s
m i s s i n g
2 4
2 - - - - - - 1 6
o f
P c t
R e s p o n s e s 3 1 . 1 2 . 2 5. 1 8 . 1 2 .
3 5
0 8 5 - - - - 1 0 0 . 0
o f C a s e s
7 1 2 8 57 42 2 8
. 4 . 6 . 1 . 9 . 6 - - - - 2 2 8 . 6
c a s e s ; 7 v a l i d c a s e s . 0 % 9 ) % ; " E 1 D " ! < , 1 $ F
3 E Val u e Label " 3 X3 X2 X1 = % 2 / . 3 A : 6 =
. + # , 0 <- 1 , 6
? "
Multiple R esponse C rossta b s ( 2 – 16 )
E l ement ar y Var iabl es % " ? . # L ; "
. < ) , " M u l t ip l e r esp o nse Set s ) : 2 #
25 6
0 ! ; 1 G 1 " ) <- ' K (
0 # # % 1 > 0
1 ) 2 @ + Co l o r ed H F (
1
1
# @ 0 # % C @ & 1 (
# @ 0 - A 0
# @ 0 ;
: " Dat a E d it o r $ $ B abyl o n j amh o r ya al ir aq q ad issya t h 1 0 1 1 1 1 0 0 0 0 1 0 1 0 0 1 0 1 1 0 1 0 0 1 1 0 1 0 + # ' 1 H ! # @ 0 1 (? .
% , 6 7 . H ! 0 ! # ; o wr a co l o r ed 0 1 0 0 0 0 1 1 0 0 1 1 0 1 # ) B 4 + # ; G
.
# @ 0 @
# @ 0 # + co l o r ed " B #
# @ 0 # $ p ap er 9 ) % 1 - 3 C B E l ement ar y Var iabl e % ; " E 1 # # 9 . > 0 1 3 F <- ; J H !
9 ) % 0 ; " 3 D < " 3 ) M u l t ip l e d ich o t o my met h o d 0 % 9 ) .( M u l t ip l e Cat ego r y M et h o d
# @ 0 % H 0 ! H ! # @ 0 % 7 1 ? . # !
: % . ? 1 9 3
, 6 Anal yze M u l t ip l e Resp o nse Cr o sst abs . $ : " D 1
+ M u l t ip l e Resp o nse Cr o sst abs
K (0، 1) co l o r ed % 0 C C " 3 ; D < " 3 . F = 3 !
Def ine Ranges 4 1
. # C " 3 # ! O K
*
*
*
C
R
O
S
S
$ P A P E R ( t a b u l a t i n g b y C O L O R E D
25 7
T
A
1 )
B
U
L
A
T
I
O
N
*
*
*
4 3
1 A ? . # 3 H !
# % C " 3 # !
: % 6 = .1
( C a ses % - ) respond ent s 1 1 responses % 1 - $ E M u l t i pl e R esponse C rosst a b s !
O pt i ons 4 1 K
:P erc ent a g es B a sed on
C a ses % - 1 ) H ! C " 3 # ! (
: C a ses
•
: R esponses
•
. (7 # 3 ) R espond ent s 1
% 1 - 1 ) H ! C " 3 # ! ( . ( 16
!
# % 1 - 3 )R esponses
O pt i ons 4 1 ? . # = " # 1 C " 3 # !
:C el l P erc ent a g es % $ E M u l t i pl e R esponse C rosst a b s . H ! % N 1 " (
. ) % N 1 " (
. " % N 1 " (
25 8
) : R ow
) : C ol u m n ) : T ot a l
• • •
.2
3
9 ! 1 7 & 1 # ? . ; " . 1 # > 0
D 7 1 # " D a ta
E d i t or $ $ C g end er >
@ A ; F . " ! 0
1= M a l e 7 1 V a l u e L a b el 3 . 3 2 7 & # 2 # 1 )
Babylon jamhorya aliraq qadissya thowra 1 1 0 1 0 1 1
0
1 0 0 1 0 0
1 0 1 0 1 0 1
1 0 0 1 0 1 0
0
0 0
1 0 1 0
: " $ $ , 6 ( 2 = F em a l e
colored g end er 1 0 0 1 0 1 1
2
1 2 1 1 1 2
J H ! # @ 0 # $ p ap er 9 ) % 1 - 3 C B
#
% 9 ) % ; " E 1 # # 9 . > 0 1 3 F <- ;
M u ltip le 9 ) % 0 ; " 3 D < " 3 ) M u ltip le dichotomy method 0
.( C ateg ory M ethod
# @ 0 % H 0 ! H ! # @ 0 % 7 1 ? . # !
, 6 A nalyz e
: % . ? 1 >
; 9 3
M u ltip le R esp onse C rosstabs . $ : " D 1
+ M u ltip le R esp onse C rosstabs
. 1 G ender % K C olored % 0 C C " 3 6 # !
259
F = 3 !
O K
4 3 . ) ) 1 D ef ine R ang es 4 : B C "3
by C O by G E C P
L O R E D N D E R ateg ory = 1 M ale e r c e n t s a n d t o t a l s
$ P A P E R (tabu lating 1)
b a s e d
o n
r e s p o n d e n t s
# ) 4 1 3 (% - ) 1 C " 3 1 ' ; 6 -
. ( # ) 3 7 & 1 3 ( 1
26 0
26 1
