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SPSS Textbook Examples
Applied Regression Analysis by John Fox
Chapter 7: Dummy-variable regression

page 143 The summary statistics and the regression equation. 

GET FILE='D:\duncan.sav'.

REGRESSION
  /STATISTICS COEFF OUTS R ANOVA
  /DEPENDENT prestige
  /METHOD=ENTER educ income.
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 Percent of males in occupation earning $3500 or more in 1950, Percent of males in occupation in 1950 who were high-school graduates(a) . Enter
a All requested variables entered.
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .910(a) .828 .820 13.369
a Predictors: (Constant), Percent of males in occupation earning $3500 or more in 1950, Percent of males in occupation in 1950 who were high-school graduates

ANOVA(b)
Model Sum of Squares df Mean Square F Sig.
1 Regression 36180.946 2 18090.473 101.216 .000(a)
Residual 7506.699 42 178.731

Total 43687.644 44


a Predictors: (Constant), Percent of males in occupation earning $3500 or more in 1950, Percent of males in occupation in 1950 who were high-school graduates
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti



Coefficients(a)

Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) -6.065 4.272
-1.420 .163
Percent of males in occupation in 1950 who were high-school graduates .546 .098 .516 5.555 .000
Percent of males in occupation earning $3500 or more in 1950 .599 .120 .464 5.003 .000
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti 
MEANS
  TABLES=prestige BY occ_type
  /CELLS MEAN COUNT.
Case Processing Summary

Cases
Included Excluded Total
N Percent N Percent N Percent
Percent of raters in NORC study rating occupation as excellent or good in presti * Occupation type, Professional/Manag, White Collar, Blue Collar 45 100.0% 0 .0% 45 100.0%

Report
Percent of raters in NORC study rating occupation as excellent or good in presti
Occupation type, Professional/Manag, White Collar, Blue Collar Mean N
bc 22.76 21
prof 80.44 18
wc 36.67 6
Total 47.69 45 
SORT CASES BY occ_type (A).

compute d1 = 0.
compute d2 = 0.
if occ_type = 2 d1 = 1.
if occ_type = 3 d2 = 1.
execute.

REGRESSION
  /STATISTICS COEFF OUTS R ANOVA
  /DEPENDENT prestige
  /METHOD=ENTER educ income d1 d2.
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 D2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, D1(a) . Enter
a All requested variables entered.
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .956(a) .913 .904 9.744
a Predictors: (Constant), D2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, D1

ANOVA(b)
Model Sum of Squares df Mean Square F Sig.
1 Regression 39889.690 4 9972.422 105.029 .000(a)
Residual 3797.955 40 94.949

Total 43687.644 44


a Predictors: (Constant), D2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, D1
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti



Coefficients(a)

Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) -.185 3.714
-.050 .961
Percent of males in occupation in 1950 who were high-school graduates .345 .114 .326 3.040 .004
Percent of males in occupation earning $3500 or more in 1950 .598 .089 .463 6.687 .000
D1 16.658 6.993 .262 2.382 .022
D2 -14.661 6.109 -.160 -2.400 .021
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

page 150 The coefficients listed in the middle of the page. 

compute incd1 = income*d1.
compute incd2 = income*d2.
compute edud1 = educ*d1.
compute edud2 = educ*d2.
execute.

REGRESSION
  /STATISTICS COEFF OUTS R ANOVA
  /DEPENDENT prestige
  /METHOD=ENTER educ income d1 d2 incd1 edud1 incd2 edud2.
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, INCD2, Percent of males in occupation in 1950 who were high-school graduates, INCD1, D2, EDUD1(a) . Enter
a All requested variables entered.
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .961(a) .923 .906 9.647
a Predictors: (Constant), EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, INCD2, Percent of males in occupation in 1950 who were high-school graduates, INCD1, D2, EDUD1

ANOVA(b)
Model Sum of Squares df Mean Square F Sig.
1 Regression 40336.999 8 5042.125 54.174 .000(a)
Residual 3350.645 36 93.073

Total 43687.644 44


a Predictors: (Constant), EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, INCD2, Percent of males in occupation in 1950 who were high-school graduates, INCD1, D2, EDUD1
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti



Coefficients(a)

Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) -3.951 6.794
-.581 .565
Percent of males in occupation in 1950 who were high-school graduates .320 .280 .302 1.142 .261
Percent of males in occupation earning $3500 or more in 1950 .783 .131 .608 5.992 .000
D1 32.008 14.109 .503 2.269 .029
D2 -7.043 20.638 -.077 -.341 .735
INCD1 -.369 .204 -.368 -1.811 .079
EDUD1 1.859E-02 .318 .025 .058 .954
INCD2 -.360 .260 -.213 -1.388 .174
EDUD2 .107 .362 .075 .295 .770
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

page 151 Table 7.1 Regression sums of squares for several models fit to Duncan's occupational prestige data. These sums of squares are the building blocks of incremental F-tests for the main and interaction effects of the independent variables. The following code is used for "terms" in the model: E, education; I, income; T, occupational type.

page 151 Table 7.2 Analysis of variance table, showing incremental F-tests for the terms in Duncan's occupational prestige regression.

NOTE: In order to get the values shown in Table 7.2, you need to use the /METHOD = test() subcommand in the regression command. Instead of running the regressions twice, we have included them with the regressions needed for Table 7.1. Note that the variables included in the the /METHOD=test subcommands are not included in the /METHOD=ENTER subcommand, but SPSS includes them in the regression as if they were. Also note that you need to look for the regression sums of squares on the first row of the ANOVA table when you do not use the /METHOD=test subcommand, and on the second line of the Model 2 section of the ANOVA table when the /METHOD=test subcommand is used.

Model 1 and row 6 of Table 7.2 (residuals): 

REGRESSION
  /STATISTICS COEFF OUTS R ANOVA
  /DEPENDENT prestige
  /METHOD=ENTER educ income d1 d2 incd1 edud1 incd2 edud2.
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, INCD2, Percent of males in occupation in 1950 who were high-school graduates, INCD1, D2, EDUD1(a) . Enter
a All requested variables entered.
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .961(a) .923 .906 9.647
a Predictors: (Constant), EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, INCD2, Percent of males in occupation in 1950 who were high-school graduates, INCD1, D2, EDUD1

ANOVA(b)
Model Sum of Squares df Mean Square F Sig.
1 Regression 40336.999 8 5042.125 54.174 .000(a)
Residual 3350.645 36 93.073

Total 43687.644 44


a Predictors: (Constant), EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, INCD2, Percent of males in occupation in 1950 who were high-school graduates, INCD1, D2, EDUD1
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti



Coefficients(a)

Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) -3.951 6.794
-.581 .565
Percent of males in occupation in 1950 who were high-school graduates .320 .280 .302 1.142 .261
Percent of males in occupation earning $3500 or more in 1950 .783 .131 .608 5.992 .000
D1 32.008 14.109 .503 2.269 .029
D2 -7.043 20.638 -.077 -.341 .735
INCD1 -.369 .204 -.368 -1.811 .079
EDUD1 1.859E-02 .318 .025 .058 .954
INCD2 -.360 .260 -.213 -1.388 .174
EDUD2 .107 .362 .075 .295 .770
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model 2 and row 5 (Income by type): 

REGRESSION
  /STATISTICS COEFF OUTS R ANOVA
  /DEPENDENT prestige
  /METHOD=ENTER income educ d1 d2 edud1 edud2
  /METHOD=test(incd1 incd2 ).
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, Percent of males in occupation in 1950 who were high-school graduates, D2, EDUD1(a) . Enter
2 INCD2, INCD1 . Test
a All requested variables entered.
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .956(a) .915 .901 9.898
2 .961(b) .923 .906 9.647
a Predictors: (Constant), EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, Percent of males in occupation in 1950 who were high-school graduates, D2, EDUD1
b Predictors: (Constant), EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, Percent of males in occupation in 1950 who were high-school graduates, D2, EDUD1, INCD2, INCD1

ANOVA(d)
Model Sum of Squares df Mean Square F Sig. R Square Change
1 Regression 39964.826 6 6660.804 67.989 .000(a)
Residual 3722.818 38 97.969


Total 43687.644 44



2 Subset Tests INCD1, INCD2 372.173 2 186.086 1.999 .150(b) .009
Regression 40336.999 8 5042.125 54.174 .000(c)
Residual 3350.645 36 93.073


Total 43687.644 44



a Predictors: (Constant), EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, Percent of males in occupation in 1950 who were high-school graduates, D2, EDUD1
b Tested against the full model.
c Predictors in the Full Model: (Constant), EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, Percent of males in occupation in 1950 who were high-school graduates, D2, EDUD1, INCD2, INCD1.
d Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti



Coefficients(a)

Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) -3.689 6.969
-.529 .600
Percent of males in occupation earning $3500 or more in 1950 .597 .094 .463 6.353 .000
Percent of males in occupation in 1950 who were high-school graduates .484 .274 .457 1.765 .086
D1 26.569 13.971 .418 1.902 .065
D2 -17.307 17.341 -.189 -.998 .325
EDUD1 -.217 .302 -.287 -.721 .476
EDUD2 -3.841E-02 .363 -.027 -.106 .916
2 (Constant) -3.951 6.794
-.581 .565
Percent of males in occupation earning $3500 or more in 1950 .783 .131 .608 5.992 .000
Percent of males in occupation in 1950 who were high-school graduates .320 .280 .302 1.142 .261
D1 32.008 14.109 .503 2.269 .029
D2 -7.043 20.638 -.077 -.341 .735
EDUD1 1.859E-02 .318 .025 .058 .954
EDUD2 .107 .362 .075 .295 .770
INCD1 -.369 .204 -.368 -1.811 .079
INCD2 -.360 .260 -.213 -1.388 .174
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti





Excluded Variables(b)

Beta In t Sig. Partial Correlation Collinearity Statistics
Model Tolerance
1 INCD1 -.277(a) -1.422 .163 -.228 5.749E-02
INCD2 -.123(a) -.824 .415 -.134 .101
a Predictors in the Model: (Constant), EDUD2, Percent of males in occupation earning $3500 or more in 1950, D1, Percent of males in occupation in 1950 who were high-school graduates, D2, EDUD1
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model 3 and row 3 of Table 7.2 (Type): 

REGRESSION
  /STATISTICS COEFF OUTS R ANOVA
  /DEPENDENT prestige
  /METHOD=ENTER educ income incd1 incd2
  /METHOD=TEST(d1 d2).
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 INCD2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, INCD1(a) . Enter
2 D2, D1 . Test
a All requested variables entered.
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .950(a) .902 .892 10.364
2 .961(b) .923 .911 9.406
a Predictors: (Constant), INCD2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, INCD1
b Predictors: (Constant), INCD2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, INCD1, D2, D1

ANOVA(d)
Model Sum of Squares df Mean Square F Sig. R Square Change
1 Regression 39390.970 4 9847.742 91.678 .000(a)
Residual 4296.675 40 107.417


Total 43687.644 44



2 Subset Tests D1, D2 934.470 2 467.235 5.281 .009(b) .021
Regression 40325.439 6 6720.907 75.960 .000(c)
Residual 3362.205 38 88.479


Total 43687.644 44



a Predictors: (Constant), INCD2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, INCD1
b Tested against the full model.
c Predictors in the Full Model: (Constant), INCD2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, INCD1, D2, D1.
d Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti



Coefficients(a)

Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) -3.912 4.572
-.855 .397
Percent of males in occupation in 1950 who were high-school graduates .465 .107 .439 4.329 .000
Percent of males in occupation earning $3500 or more in 1950 .673 .120 .522 5.624 .000
INCD1 7.535E-02 .133 .075 .568 .573
INCD2 -.415 .131 -.245 -3.181 .003
2 (Constant) -4.732 4.157
-1.138 .262
Percent of males in occupation in 1950 who were high-school graduates .357 .113 .337 3.174 .003
Percent of males in occupation earning $3500 or more in 1950 .776 .118 .602 6.570 .000
INCD1 -.370 .183 -.369 -2.017 .051
INCD2 -.360 .249 -.213 -1.449 .155
D1 31.712 10.166 .499 3.120 .003
D2 -1.637 13.222 -.018 -.124 .902
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti





Excluded Variables(b)

Beta In t Sig. Partial Correlation Collinearity Statistics
Model Tolerance
1 D1 .503(a) 3.289 .002 .466 8.428E-02
D2 -.127(a) -.824 .415 -.131 .103
a Predictors in the Model: (Constant), INCD2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, INCD1
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model 4: 

REGRESSION
  /STATISTICS COEFF OUTS R ANOVA
  /DEPENDENT prestige
  /METHOD=ENTER educ income d1 d2.
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 D2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, D1(a) . Enter
a All requested variables entered.
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .956(a) .913 .904 9.744
a Predictors: (Constant), D2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, D1

ANOVA(b)
Model Sum of Squares df Mean Square F Sig.
1 Regression 39889.690 4 9972.422 105.029 .000(a)
Residual 3797.955 40 94.949

Total 43687.644 44


a Predictors: (Constant), D2, Percent of males in occupation in 1950 who were high-school graduates, Percent of males in occupation earning $3500 or more in 1950, D1
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti



Coefficients(a)

Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) -.185 3.714
-.050 .961
Percent of males in occupation in 1950 who were high-school graduates .345 .114 .326 3.040 .004
Percent of males in occupation earning $3500 or more in 1950 .598 .089 .463 6.687 .000
D1 16.658 6.993 .262 2.382 .022
D2 -14.661 6.109 -.160 -2.400 .021
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model 5 and row 2 of Table 7.2 (Income):  

REGRESSION
  /STATISTICS COEFF OUTS R ANOVA
  /DEPENDENT prestige
  /METHOD=ENTER educ income
  /METHOD=TEST(income).
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 Percent of males in occupation earning $3500 or more in 1950, Percent of males in occupation in 1950 who were high-school graduates(a) . Enter
a All requested variables entered.
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .910(a) .828 .820 13.369
a Predictors: (Constant), Percent of males in occupation earning $3500 or more in 1950, Percent of males in occupation in 1950 who were high-school graduates

ANOVA(b)
Model Sum of Squares df Mean Square F Sig.
1 Regression 36180.946 2 18090.473 101.216 .000(a)
Residual 7506.699 42 178.731

Total 43687.644 44


a Predictors: (Constant), Percent of males in occupation earning $3500 or more in 1950, Percent of males in occupation in 1950 who were high-school graduates
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti



Coefficients(a)

Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) -6.065 4.272
-1.420 .163
Percent of males in occupation in 1950 who were high-school graduates .546 .098 .516 5.555 .000
Percent of males in occupation earning $3500 or more in 1950 .599 .120 .464 5.003 .000
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model 6 and row 4 of Table 7.2 (Education by type): 

REGRESSION
  /STATISTICS COEFF OUTS R ANOVA
  /DEPENDENT prestige
  /METHOD=ENTER educ d1 d2
  /METHOD=TEST(edud1 edud2).
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 D2, Percent of males in occupation in 1950 who were high-school graduates, D1(a) . Enter
2 EDUD2, EDUD1 . Test
a All requested variables entered.
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .903(a) .816 .802 14.007
2 .908(b) .824 .802 14.030
a Predictors: (Constant), D2, Percent of males in occupation in 1950 who were high-school graduates, D1
b Predictors: (Constant), D2, Percent of males in occupation in 1950 who were high-school graduates, D1, EDUD2, EDUD1

ANOVA(d)
Model Sum of Squares df Mean Square F Sig. R Square Change
1 Regression 35643.566 3 11881.189 60.557 .000(a)
Residual 8044.078 41 196.197


Total 43687.644 44



2 Subset Tests EDUD1, EDUD2 367.424 2 183.712 .933 .402(b) .008
Regression 36010.990 5 7202.198 36.590 .000(c)
Residual 7676.654 39 196.837


Total 43687.644 44



a Predictors: (Constant), D2, Percent of males in occupation in 1950 who were high-school graduates, D1
b Tested against the full model.
c Predictors in the Full Model: (Constant), D2, Percent of males in occupation in 1950 who were high-school graduates, D1, EDUD2, EDUD1.
d Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti



Coefficients(a)

Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) 8.469 5.004
1.693 .098
Percent of males in occupation in 1950 who were high-school graduates .564 .156 .533 3.608 .001
D1 26.088 9.846 .410 2.650 .011
D2 -6.500 8.604 -.071 -.755 .454
2 (Constant) -2.854 9.877
-.289 .774
Percent of males in occupation in 1950 who were high-school graduates 1.011 .371 .955 2.728 .010
D1 42.660 19.476 .671 2.190 .035
D2 16.219 23.415 .177 .693 .493
EDUD1 -.512 .422 -.676 -1.211 .233
EDUD2 -.632 .498 -.443 -1.270 .212
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti





Excluded Variables(b)

Beta In t Sig. Partial Correlation Collinearity Statistics
Model Tolerance
1 EDUD1 -.213(a) -.500 .620 -.079 2.526E-02
EDUD2 -.167(a) -.628 .533 -.099 6.461E-02
a Predictors in the Model: (Constant), D2, Percent of males in occupation in 1950 who were high-school graduates, D1
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model 7 and row 1 of Table 7.2 (Education): 

REGRESSION
  /STATISTICS COEFF OUTS R ANOVA
  /DEPENDENT prestige
  /METHOD=ENTER income d1 d2 incd1 incd2
  /METHOD=TEST(educ).
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 INCD2, Percent of males in occupation earning $3500 or more in 1950, D1, D2, INCD1(a) . Enter
2 Percent of males in occupation in 1950 who were high-school graduates . Test
a All requested variables entered.
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .950(a) .903 .890 10.443
2 .961(b) .923 .911 9.406
a Predictors: (Constant), INCD2, Percent of males in occupation earning $3500 or more in 1950, D1, D2, INCD1
b Predictors: (Constant), INCD2, Percent of males in occupation earning $3500 or more in 1950, D1, D2, INCD1, Percent of males in occupation in 1950 who were high-school graduates

ANOVA(d)
Model Sum of Squares df Mean Square F Sig. R Square Change
1 Regression 39434.135 5 7886.827 72.314 .000(a)
Residual 4253.510 39 109.064


Total 43687.644 44



2 Subset Tests Percent of males in occupation in 1950 who were high-school graduates 891.305 1 891.305 10.074 .003(b) .020
Regression 40325.439 6 6720.907 75.960 .000(c)
Residual 3362.205 38 88.479


Total 43687.644 44



a Predictors: (Constant), INCD2, Percent of males in occupation earning $3500 or more in 1950, D1, D2, INCD1
b Tested against the full model.
c Predictors in the Full Model: (Constant), INCD2, Percent of males in occupation earning $3500 or more in 1950, D1, D2, INCD1, Percent of males in occupation in 1950 who were high-school graduates.
d Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti



Coefficients(a)

Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta
1 (Constant) 2.683 3.818
.703 .486
Percent of males in occupation earning $3500 or more in 1950 .845 .129 .655 6.554 .000
D1 44.487 10.364 .699 4.292 .000
D2 14.853 13.499 .162 1.100 .278
INCD1 -.291 .202 -.290 -1.442 .157
INCD2 -.467 .274 -.276 -1.709 .095
2 (Constant) -4.732 4.157
-1.138 .262
Percent of males in occupation earning $3500 or more in 1950 .776 .118 .602 6.570 .000
D1 31.712 10.166 .499 3.120 .003
D2 -1.637 13.222 -.018 -.124 .902
INCD1 -.370 .183 -.369 -2.017 .051
INCD2 -.360 .249 -.213 -1.449 .155
Percent of males in occupation in 1950 who were high-school graduates .357 .113 .337 3.174 .003
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti





Excluded Variables(b)

Beta In t Sig. Partial Correlation Collinearity Statistics
Model Tolerance
1 Percent of males in occupation in 1950 who were high-school graduates .337(a) 3.174 .003 .458 .179
a Predictors in the Model: (Constant), INCD2, Percent of males in occupation earning $3500 or more in 1950, D1, D2, INCD1
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti

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