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.
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 highschool 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  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 highschool graduates 
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 highschool graduates  
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti 

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 highschool 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.

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% 
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.
Model  Variables Entered  Variables Removed  Method 

1  D2, Percent of males in occupation in 1950 who were highschool 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  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 highschool graduates, Percent of males in occupation earning $3500 or more in 1950, D1 
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 highschool 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 

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 highschool 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.
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 highschool 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  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 highschool graduates, INCD1, D2, EDUD1 
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 highschool graduates, INCD1, D2, EDUD1  
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti 

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 highschool 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  1.859E02  .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 Ftests 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 Ftests 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 /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.
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 highschool 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  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 highschool graduates, INCD1, D2, EDUD1 
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 highschool graduates, INCD1, D2, EDUD1  
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti 

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 highschool 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  1.859E02  .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 ).
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 highschool 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  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 highschool 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 highschool graduates, D2, EDUD1, INCD2, INCD1 
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 highschool 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 highschool graduates, D2, EDUD1, INCD2, INCD1.  
d Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti 

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 highschool 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  3.841E02  .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 highschool 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  1.859E02  .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 

Beta In  t  Sig.  Partial Correlation  Collinearity Statistics  

Model  Tolerance  
1  INCD1  .277(a)  1.422  .163  .228  5.749E02 
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 highschool 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).
Model  Variables Entered  Variables Removed  Method 

1  INCD2, Percent of males in occupation in 1950 who were highschool 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  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 highschool 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 highschool graduates, Percent of males in occupation earning $3500 or more in 1950, INCD1, D2, D1 
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 highschool 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 highschool 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 

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 highschool 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  7.535E02  .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 highschool 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 

Beta In  t  Sig.  Partial Correlation  Collinearity Statistics  

Model  Tolerance  
1  D1  .503(a)  3.289  .002  .466  8.428E02 
D2  .127(a)  .824  .415  .131  .103  
a Predictors in the Model: (Constant), INCD2, Percent of males in occupation in 1950 who were highschool 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.
Model  Variables Entered  Variables Removed  Method 

1  D2, Percent of males in occupation in 1950 who were highschool 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  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 highschool graduates, Percent of males in occupation earning $3500 or more in 1950, D1 
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 highschool 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 

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 highschool 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).
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 highschool 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  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 highschool graduates 
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 highschool graduates  
b Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti 

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 highschool 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).
Model  Variables Entered  Variables Removed  Method 

1  D2, Percent of males in occupation in 1950 who were highschool 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  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 highschool graduates, D1  
b Predictors: (Constant), D2, Percent of males in occupation in 1950 who were highschool graduates, D1, EDUD2, EDUD1 
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 highschool 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 highschool graduates, D1, EDUD2, EDUD1.  
d Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti 

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 highschool 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 highschool 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 

Beta In  t  Sig.  Partial Correlation  Collinearity Statistics  

Model  Tolerance  
1  EDUD1  .213(a)  .500  .620  .079  2.526E02 
EDUD2  .167(a)  .628  .533  .099  6.461E02  
a Predictors in the Model: (Constant), D2, Percent of males in occupation in 1950 who were highschool 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).
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 highschool 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  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 highschool graduates 
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 highschool 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 highschool graduates.  
d Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti 

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 highschool graduates  .357  .113  .337  3.174  .003  
a Dependent Variable: Percent of raters in NORC study rating occupation as excellent or good in presti 

Beta In  t  Sig.  Partial Correlation  Collinearity Statistics  

Model  Tolerance  
1  Percent of males in occupation in 1950 who were highschool 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 