25 SPSS 14 SPSS E-mail: [email protected]
YA
2
?
3
, ?
, ?4
5
()
( ) () () 6
SPSS
()
7
90 80 70 60 50 40 30 20 10 0
8
t (ANOVA) () (MANOVA)
logistic) 9
dont reject
10
MANOVA ANOVA t
Y()
()
X
()
11
x
?? ?? ?
y
y x x A M Y B xn
12
1.
P m (mp) (parsimony)
2.
13
(error)
14
15
(assumptions) specific factor
16
spss 1
17
18
vs. Formative indicator Reflective indicator
X1 X2 X3 X4 X5 X6
Y1 Y2 Y3 Y4
P1
F1
P2
F2
Y5 Y619
CFA PCA CFA
(2002),.. ,p107-13220
()
21
F1 x2 x3 x4 x1
F2
x5 x6
22
()
200 (100) 200 K-means
(cluster analysis) 23
one way MANOVA
one way MANOVA
24
520 (multivariate data analysis, 5th ed., Hair, Jr. et al)
1 .9 6 s n = 2 en = 1 .9 62
2
2
p (1 p ) e225
26
4060 t (CR) 0.5 0.3
CR
27
(pretest):
:() () () ()
28
excel tip: 29
key in
30
(chi-square test)()
31
t (t-test)
32
ANOVA
Y1 = X1 + X233
(MANOVA) MANOVA MANOVAANOVA (Bryman & Cramer, 1997)
Y1 + Y2 + ... = X 1 + X 2 + ...34
()F F BonferroniLSDLSD p-valueN(N-1)/20.05
Scheffe method()
Tukey HSD method()35
()S-N-K (Student-Newman-Keuls)Tukey
DuncanS-N-K
Games-Howell methodN
DunnettHilton A & Armstrong R A (2006) Is one set of data
more variable than another? Microbiologist Vol. 7: No.2 34-36 (June
2006)
36
()correlation coefficient of correlation -11
37
1
Y
Zero-Order)YX1 (23)/(1234)5 X1
2
4 3 6 7 X2
Partial Correlations YX1(2/12) YX2(4/14)
(Semi-Partial Correlations)X1,X2, X1 (2/1234)X2(4/1234) Y38
(Regression): (linear relationship) x y 1. 2. xy 3. (x)(y)
Y1 = aX 1 + bX 2 + ...
39
path analysis : n 0.95n A M B40
Y
(canonical)x y
Y1 + Y2 = X 1 + X 2 + ... 41
x1
y1
x2
y2
42
Logistic
43
(discriminate analysis)
Y1 = X1 + X2 + ...44
()()
45
()()
46
1.() 2. 3. 4. 5.
47
48
49
50
(Dummy Variables)=(n) -1 : DV(0,0,0) (1,0,0) (0,1,0) (0,0,1)
(0,0,0)
51
52
