The data set CAMPUS from Wooldridge is collected by an undergraduate Michigan State University student for his project to analyze campus crime rates across the U.S. In this data, lerime denotes the logarithm of the number of crimes committed in a year in the university campus; lenroll denotes the logarithm of the total number of students enrolled in the university; Ipolice denotes the logarithm of the number of police officers employed by the university; private is a dummy variable indicating whether the university is private. The econometric model is given by: lcrime = Bo + Bilenroll + Bzlpolice + Baprivate + u. Assume that all the classical linear regression model assumptions are satisfied. The regression output is provided below. Parts of the output are intentionally withheld. reg lerime lenroll 1police priv Source df MS Number of obs 97 F(3, 93) Prob > F 54.04 Model | Residual | 0.0000 R-squared Adj R-squared Root MSE 0.6237 84721 Total | 183.119479 lcrime | Coef. Std. Err. [954 Conf. Interval] lenroll I 1police | priv | cons -5.102549 -9462363 -5391599 .26656 6.48 3.58 0.94 -4.40 .1460992 .1507161 0.000 0.001 0.350 0.000 .6561123 .2398675 1.23636 .9384523 .9297305 .2835986 -.2966105 1.160198 -7.406473 -2.798626 a. (3 points) Explain why it is crucial to assume that all the classical linear regression model assumptions are satisfied for this question. b. (3 points) State the null and alternative hypothesis to test whether the elasticity of crime with respect to enrollment is unity. c. (3 points) Conduct the test in part b. d. (4 points) Interpret the slope coefficient for private. e. (5 points) Regressing lenroll on Ipolice yields an R of 0.5848. Do you reject Ho: B-B3=0 at the 10 percent level of significance?