The following data were obtained from a sample of 12 respondents. Suppose that we started by calculating a bivariate regression equation which predicted children's education using information on fathers' education. Suppose further that we then calculated a multiple regression equation which predicted children's education using information on both fathers' education and mothers' education. What would you expect to happen to the sum of squares regression in the multiple regression equation relative to the sum of squares regression in the bivariate linear regression equation? Does it increase or decrease in value? Why?
Highest Grade of School Completed (Respondent)Highest Grade of School Completed (Father)Highest Grade of School Completed (Mother)1212121410121414121088141212161212151051266161620141313151412141414 Mean13.8311.7511.50St. Dev.1.752.903.90Variance3.068.0215.18
What will be an ideal response?
The sum of squares regression increased in value.
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