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

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 /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