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Suppose we have a data set with five predictors, X1 = GPA, X2 = IQ, X3 = Level (1 for College and 0 for High
Suppose we have a data set with five predictors, X1 = GPA, X2 = IQ, X3 = Level (1 for College and 0 for High School), X4 = Interaction between GPA and IQ, and X5 = Interaction between GPA and Level. The response is starting salary after graduation (in thousands of dollars). Salary = Bo + BIGPA + 82IQ + B:Level + BAGPA . IQ + B;GPA . Level + e Suppose we use least squares to fit the model, and get Bo = 40, 81 = 16, 82 = 0.07, 83 = 35, 84 = 0, 85 = -8. Also, assume that all coefficient estimates are statistically significant at conventional significance level. Keeping all other factors fixed, what is the estimated impact of one unit increase in GPA on the starting salary of a college graduate
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