Section 3.4.1 used x1 = size of house and x2 = whether new to predict y = selling price. Suppose we instead use a GLM, log(????i) = ????0 + ????1 log(xi1) +

????2xi2.

a. For this GLM, interpret ????1 and ????2. (Hint: Adjusting for the other variable, find multiplicative effects on ????i of (i) changing xi2 from 0 to 1, (ii) increasing xi1 by 1%.)

b. Fit the GLM, assuming normality for {yi}, and interpret. Compare the predictive power of this model with the linear model of Section 3.4.1 by finding R = corr(y, ????̂) for each model.

c. For this GLM or the corresponding LM for E[log( yi)], refit the model without the most influential observation and summarize. Also, determine whether the fit improves significantly by permitting interaction between log(xi1) and xi2.