Preference Analysis of Cars
Car Makes - Symmetric Biplot (Alpha=1/2)

Standardization Type: MEAN (VARDEF = N - 1 )

Singular values and variance accounted for

Singular Values Percent Cum % Histogram of %
40.9372 45.70 45.70 ****************************************
29.6861 24.03 69.73 *********************
15.0533 6.18 75.91 *****
14.8005 5.97 81.89 *****
12.6845 4.39 86.27 ****
11.5476 3.64 89.91 ***
10.3740 2.93 92.84 ***
9.3794 2.40 95.24 **
7.5872 1.57 96.81 *
6.4207 1.12 97.94 *
5.5715 0.85 98.78 *
4.2083 0.48 99.27 *
3.7332 0.38 99.65 *
2.4011 0.16 99.80 *
2.1026 0.12 99.92 *
1.6691 0.08 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *

OBS / VARS ratio: 1.184863 Scale: 1

Biplot Factor Type

Symmetric

Biplot coordinates

  DIM1 DIM2
OBS CADILLAC -1.0890 2.8099
OBS CHEVROLET -1.2400 -1.6682
OBS CHEVROLET -0.3487 -1.1789
OBS CHEVROLET -0.8458 -0.1667
OBS FORD -0.8535 -1.1648
OBS FORD -0.6958 0.0810
OBS FORD -1.5640 -1.6802
OBS HONDA 2.2930 0.2011
OBS HONDA 1.6175 -0.9371
OBS LINCOLN -1.1538 2.8987
OBS PLYMOUTH -1.5383 0.1045
OBS PLYMOUTH -0.7050 -0.7334
OBS PLYMOUTH -0.9415 -0.5016
OBS PONTIAC -0.6369 1.5712
OBS VOLKSWAGEN 2.3160 0.3295
OBS VOLKSWAGEN 2.1976 -0.5758
OBS VOLVO 3.1881 0.6108
VAR J1 2.3876 -0.0198
VAR J2 0.4785 1.1259
VAR J3 1.2194 -0.6201
VAR J4 0.7679 1.1883
VAR J5 1.2301 1.8909
VAR J6 0.9281 2.5777
VAR J7 1.6738 -0.5045
VAR J8 0.4474 -0.0706
VAR J9 -0.8273 1.5006
VAR J10 1.4685 -0.4855
VAR J11 1.5722 0.1970
VAR J12 1.6258 -0.3870
VAR J13 1.9949 -0.1488
VAR J14 1.4989 0.2107
VAR J15 1.7717 -0.5971
VAR J16 0.0467 1.4606
VAR J17 0.2342 1.3605
VAR J18 1.1957 1.0137
VAR J19 1.4881 0.1623
VAR J20 1.2338 -1.2318
VAR J21 0.1949 1.1493
VAR J22 0.2044 -0.6558
VAR J23 -1.6633 1.0337
VAR J24 -0.4416 -1.8515
VAR J25 -1.4031 0.4893


Biplot of Cars


Preference Analysis of Cars
Car Source - Symmetric Biplot (Alpha=1/2)

Standardization Type: MEAN (VARDEF = N - 1 )

Singular values and variance accounted for

Singular Values Percent Cum % Histogram of %
40.9372 45.70 45.70 ****************************************
29.6861 24.03 69.73 *********************
15.0533 6.18 75.91 *****
14.8005 5.97 81.89 *****
12.6845 4.39 86.27 ****
11.5476 3.64 89.91 ***
10.3740 2.93 92.84 ***
9.3794 2.40 95.24 **
7.5872 1.57 96.81 *
6.4207 1.12 97.94 *
5.5715 0.85 98.78 *
4.2083 0.48 99.27 *
3.7332 0.38 99.65 *
2.4011 0.16 99.80 *
2.1026 0.12 99.92 *
1.6691 0.08 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *

OBS / VARS ratio: 1.184863 Scale: 1

Biplot Factor Type

Symmetric

Biplot coordinates

  DIM1 DIM2
OBS US -1.0890 2.8099
OBS US -1.2400 -1.6682
OBS US -0.3487 -1.1789
OBS US -0.8458 -0.1667
OBS US -0.8535 -1.1648
OBS US -0.6958 0.0810
OBS US -1.5640 -1.6802
OBS IMPORT 2.2930 0.2011
OBS IMPORT 1.6175 -0.9371
OBS US -1.1538 2.8987
OBS US -1.5383 0.1045
OBS US -0.7050 -0.7334
OBS US -0.9415 -0.5016
OBS US -0.6369 1.5712
OBS IMPORT 2.3160 0.3295
OBS IMPORT 2.1976 -0.5758
OBS IMPORT 3.1881 0.6108
VAR J1 2.3876 -0.0198
VAR J2 0.4785 1.1259
VAR J3 1.2194 -0.6201
VAR J4 0.7679 1.1883
VAR J5 1.2301 1.8909
VAR J6 0.9281 2.5777
VAR J7 1.6738 -0.5045
VAR J8 0.4474 -0.0706
VAR J9 -0.8273 1.5006
VAR J10 1.4685 -0.4855
VAR J11 1.5722 0.1970
VAR J12 1.6258 -0.3870
VAR J13 1.9949 -0.1488
VAR J14 1.4989 0.2107
VAR J15 1.7717 -0.5971
VAR J16 0.0467 1.4606
VAR J17 0.2342 1.3605
VAR J18 1.1957 1.0137
VAR J19 1.4881 0.1623
VAR J20 1.2338 -1.2318
VAR J21 0.1949 1.1493
VAR J22 0.2044 -0.6558
VAR J23 -1.6633 1.0337
VAR J24 -0.4416 -1.8515
VAR J25 -1.4031 0.4893


Biplot of Cars


Preference Analysis of Cars
Car Models - Symmetric Biplot (Alpha=1/2)

Standardization Type: MEAN (VARDEF = N - 1 )

Singular values and variance accounted for

Singular Values Percent Cum % Histogram of %
40.9372 45.70 45.70 ****************************************
29.6861 24.03 69.73 *********************
15.0533 6.18 75.91 *****
14.8005 5.97 81.89 *****
12.6845 4.39 86.27 ****
11.5476 3.64 89.91 ***
10.3740 2.93 92.84 ***
9.3794 2.40 95.24 **
7.5872 1.57 96.81 *
6.4207 1.12 97.94 *
5.5715 0.85 98.78 *
4.2083 0.48 99.27 *
3.7332 0.38 99.65 *
2.4011 0.16 99.80 *
2.1026 0.12 99.92 *
1.6691 0.08 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *
0.0000 0.00 100.00 *

OBS / VARS ratio: 1.184863 Scale: 1

Biplot Factor Type

Symmetric

Biplot coordinates

  DIM1 DIM2
OBS ELDORADO -1.0890 2.8099
OBS CHEVETTE -1.2400 -1.6682
OBS CITATION -0.3487 -1.1789
OBS MALIBU -0.8458 -0.1667
OBS FAIRMONT -0.8535 -1.1648
OBS MUSTANG -0.6958 0.0810
OBS PINTO -1.5640 -1.6802
OBS ACCORD 2.2930 0.2011
OBS CIVIC 1.6175 -0.9371
OBS CONTINENTAL -1.1538 2.8987
OBS GRAN FURY -1.5383 0.1045
OBS HORIZON -0.7050 -0.7334
OBS VOLARE -0.9415 -0.5016
OBS FIREBIRD -0.6369 1.5712
OBS DASHER 2.3160 0.3295
OBS RABBIT 2.1976 -0.5758
OBS DL 3.1881 0.6108
VAR J1 2.3876 -0.0198
VAR J2 0.4785 1.1259
VAR J3 1.2194 -0.6201
VAR J4 0.7679 1.1883
VAR J5 1.2301 1.8909
VAR J6 0.9281 2.5777
VAR J7 1.6738 -0.5045
VAR J8 0.4474 -0.0706
VAR J9 -0.8273 1.5006
VAR J10 1.4685 -0.4855
VAR J11 1.5722 0.1970
VAR J12 1.6258 -0.3870
VAR J13 1.9949 -0.1488
VAR J14 1.4989 0.2107
VAR J15 1.7717 -0.5971
VAR J16 0.0467 1.4606
VAR J17 0.2342 1.3605
VAR J18 1.1957 1.0137
VAR J19 1.4881 0.1623
VAR J20 1.2338 -1.2318
VAR J21 0.1949 1.1493
VAR J22 0.2044 -0.6558
VAR J23 -1.6633 1.0337
VAR J24 -0.4416 -1.8515
VAR J25 -1.4031 0.4893


Biplot of Cars


Preference Analysis of Cars
Car Models - Symmetric Biplot (Alpha=1/2)
Correlations Between Component Scores and Car Attributes

The CORR Procedure

10 With Variables: MPG Reliable Accel Braking Handling Ride Visible Comfort Quiet Cargo
2 Variables: DIM1 DIM2

Pearson Correlation Coefficients, N = 17
  DIM1 DIM2
MPG 0.60558 -0.49903
Reliable 0.71493 0.07910
Accel 0.18750 0.18383
Braking 0.27273 -0.49041
Handling 0.58817 0.16310
Ride 0.11496 0.55193
Visible 0.40948 -0.52502
Comfort 0.24652 0.36435
Quiet 0.23513 0.58765
Cargo 0.25678 -0.03032


Plot of DIM2 * DIM1 = _type_