1. FASDFASDFD
-10 -5 0 5 10
0.3
10
0.2
96
98 95 106 107
105
23 24 32
34 85
5
97
33 92 31 Z.NH
0.1
94 112
7257 37 27
67 6830
66 25 104110 89
52
39 28
42 40 90 99
Comp. 2
77 51
93 26 55108 101 109 Z.ALT..VP 91
46
75 6941 59 22
76 71 103 100 86
0.0
73 56 35 11
50
0
88
87
38 78 43
29 14 45
54 53 111 102
47 Z.NR
6465
62 63
74 61 49 48 7
8 44
12 6
70 58 82 19 81 4
79 84 80
-0.1
15
36 3
2113
-5
60
83 20 16 9 10 2
18
-0.2
1
17 Z.N.N 5
-10
-0.2 -0.1 0.0 0.1 0.2 0.3
Comp. 1
BIPLOTS

2. Relative Importance of Principal Components
1.4
1.2 0.362
0.616
1.0
0.845
Variances
0.8
1
0.6
0.4
0.2
0.0
Comp. 1 Comp. 2 Comp. 3 Comp. 4
HKHKHK

3. Comp. 1
0.4
0.0
Z.NR Z.ALT..VP Z.NH Z.N.N
Comp. 2
0.0
-0.8
Z.N.N Z.NH Z.ALT..VP Z.NR
Comp. 3
0.0
-0.8
Z.NH Z.ALT..VP Z.N.N Z.NR
Comp. 4
0.2
-0.6
Z.NR Z.ALT..VP Z.N.N Z.NH
MNBM,B,M
*** Principal Components Analysis ***
Standard deviations:
Comp. 1 Comp. 2 Comp. 3 Comp. 4
1.197909 1.002803 0.9530428 0.7844711
The number of variables is 4 and the number of observations is 112
Component names:
"sdev" "loadings" "correlations" "scores" "center" "scale" "n.obs" "terms"
"call" "factor.sdev" "coef"
Call:
princomp(x = ~ Z.ALT..VP + Z.N.N + Z.NH + Z.NR, data =
DATOS..CONCENTRADOS.Y.COSTO..1, scores = T, cor = F, na.action =
na.exclude)
Importance of components:
Comp. 1 Comp. 2 Comp. 3 Comp. 4
Standard deviation 1.1979087 1.0028034 0.9530428 0.7844711
Proportion of Variance 0.3619783 0.2536686 0.2291183 0.1552348
Cumulative Proportion 0.3619783 0.6156469 0.8447652 1.0000000

4. -2 -1 0 1 2 3 -2 -1 0 1 2
4
3
2
Z.ALT..VP 1
0
-1
-2
3
2
1
Z.N.N
0
-1
-2
2
1
Z.NH -0
-1
-2
2
1
0 Z.NR
-1
-2
-2 -1 0 1 2 3 4 -2 -1 -0 1 2