76
8135
51056
5
935
7790
58846
6
878
7318
66164
7
841
7012
73176
8
804
6702
79878
9
672
5599
85477
10
628
5234
90711
11
608
5064
95775
12
507
4225
100000
Extractio
MethodPri
cipalCompo
e
tA
alysis
Extractio
SumsofSquaredLoadi
gs
Total2872
ofVaria
ce
23931
Cumulative
23931
1177
9809
33739
Rotatio
SumsofSquaredLoadi
gs
Total2211
ofVaria
ce
18428
Cumulative
18428
1837
15311
33739
分析：上图显示三个公因子的共同度的累积方程贡献率为33739，对原始变量的解释效果较差。图111
7
fEige
value
ScreePlot
35
30
25
20
15
10
5
00123456789101112
Compo
e
tNumber
分析：上图显示公因子的特征值图112
Compo
e
tMatrixa
Compo
e
t
1
2
X23
661
180
X24
545
164
X49
540
326
X1
530
289
X46
524
184
X12
497
317
X19
482
285
X15
454
370
X29
406
108
X11
402
262
X30
366
117
X7
380
694
Extractio
MethodPri
cipalCompo
e
tA
alysisa2compo
e
tsextracted
分析：上图为因子载荷矩阵，因子载荷未集中接近于1或0，说明公因子对原始变量的解释程度较差。图113
8
fRotatedCompo
e
tMatrixa
Compo
e
t
1
2
X23
629
272
X49
625
082
X12
586
063
X19
555
078
X24
529
212
X46
524
183
X7
136
779
X15
123
572
X1
234
556
X11
151
455
X29
250
337
X30
213
320
Extractio
MethodPri
cipalCompo
e
tA
alysisRotatio
MethodVarimaxwithKaiserNormalizatio
aRotatio
co
vergedi
3iteratio
s
分析：上图为基于方差最大正交旋转以后的因子载荷矩阵，总体来看效果仍不好。图114
Compo
e
tTra
sformatio
Matrix
Compo
e
t1
2
1781
624
2624
781
Extractio
MethodPri
cipalCompo
e
tA
alysisRotatio
MethodVarimaxwithKaiserNormalizatio

图114为因子旋转的变换矩阵图115
9
fCompo
e
t2
Compo
e
tPloti
RotatedSpace
10x7
x15x1
5
x11xx3209
xx4264x23
xx1x19429
00
5
10
10
5
00
5
10
Compo
e
t1
图为旋转后的因子散点图图116
Compo
e
tScoreCoefficie
tMatrix
Compo
e
t
1
2
X1
009
307
X7
265
543
X11
029
261
X12
303
102
X15
073
344
X19
282
085
X23
275
024
X24
236
010
X29
053
160
X30
038
157
X46
240
008
X49
320
099
Extractio
MethodPri
cipalCompo
e
tA
alysisRotatio
MethodVarimaxwithKaiserNormalizatio
Compo
e
tScores
图为因子得分系数矩阵图117
10
fCompo
e
tScoreCovaria
ceMatrix
Compo
e
t1
2
11000
000
2000
1000
Extractio
MethodPri
cipalCompo
e
tA
alysisRotatio
MethodVarimaxwithKaiserNormalizatio

Compo
e
tScores
图为因子得分协方差阵
作业选用数据文件data1501，利用因子分析的新变r