C Use the data in DISCRIM.RAW to answer this question. (See also Computer Exercise C in Chapter 3.) (i) Use OLS to estimate the model log(psoda) 5 b0 1 b1prpblck 1 b2 log(income) 1 b3prppov 1 u, and report the results in the usual form. Is bˆ1 statistically different from zero at the 5% level against a two-sided alternative? What about at the 1% level? (ii) What is the correlation between log(income) and prppov? Is each variable statistically significant in any case? Report the two-sided p-values. (iii) To the regression in part (i), add the variable log(hseval). Interpret its coefficient and report the two-sided p-value for H0: blog(hseval) 5 0. (iv) In the regression in part (iii), what happens to the individual statistical significance of log(income) and prppov? Are these variables jointly significant? (Compute a p-value.) What do you make of your answers? (v) Given the results of the previous regressions, which one would you report as most reliable in determining whether the racial makeup of a zip code influences local fast-food prices?