Solution) Run a regression equation to predict father’s education from mother’s education (variables paeduc an

Question: From the regression procedure, obtain the least-squares estimates for the slope and the intercept.

a. Write the regression equation to predict a husband’s education from his wife’s education. What proportion of the variability in husband’s education can be explained by wife education?

b. The observed value for a husband’s years of education is 14 and his wife’s 13 years. What’s the residual?

Model Summary
Model	R	R Square			Adjusted R Square			Std. Error of the Estimate
1	.561^a	.314			.313			2.42481
a. Predictors: (Constant), wife's education (yrs)
ANOVA^b
Model			Sum of Squares			df			Mean Square		F		Sig.
1	Regression		1635.068			1			1635.068		278.086		.000^a
	Residual		3568.994			607			5.880
	Total		5204.062			608
a. Predictors: (Constant), wife's education (yrs)
b. Dependent Variable: husband's education (yrs)
Coefficients^a
Model				Unstandardized Coefficients						Standardized Coefficients		t		Sig.
Model				B			Std. Error			Beta		t		Sig.
1	(Constant)			5.341			.504					10.598		.000
1	wife's education (yrs)			.620			.037			.561		16.676		.000
a. Dependent Variable: husband's education (yrs)