We further explore the relationship between respondent’s education and mother’s education, computing regression models separately for males and females.
1. Calculate the regression equation for each.
2. What is the predicted value of respondent’s education when mother’s education is 20 years?
3. For which gender group is the relationship between respondent’s education and mother’s education strongest? Explain.

Transcribed Image Text:

Model Summary Adjusted R Square Std. Error of the Estimate Model 1 R R Square .450 a. sex RESPONDENTS SEX = 1 MALE .202 .201 2.834 b. Predictors: (Constant), maeduc HIGHEST YEAR SCHOOL COMPLETED, MOTHER ANOVAa.b Sum of Squares Model df Mean Square F Sig. 121.559 .000 Regression Residual 976.149 1 976.149 3846.500 479 8.030 Total 4822.649 480 a. sex RESPONDENTS SEX = 1 MALE b. Dependent Variable: educ HIGHEST YEAR OF SCHOOL COMPLETED C. Predictors: (Constant), maeduc HIGHEST YEAR SCHOOL COMPLETED, MOTHER Coefficientsb Standardized Coefficients Unstandardized Coefficients Std. Error .403 Beta Sig. .000 Model 1 (Constant) 9.768 24.258 maeduc HIGHEST YEAR SCHOOL COMPLETED, MOTHER .355 .032 .450 11.025 .000 a. sex RESPONDENTS SEX = 1 MALE b. Dependent Variable: educ HIGHEST YEAR OF SCHOOL COMPLETED