02 a (5 points) We are interested in determinants of felony arrests. We have a random sample of 2125 individuals. We have data on the number of felony arrests inforr}, the average sentence for previous convictions [ougserr]. the proportion of prior arrests that lead to convictions {pond}, income (inc. measured in 000's of USD}, time spent in prison that year {prime}, as well as total months spent in prison since 13 {rottr'me} We rst estimate the following regression [standard errors in parenthesis): m = .353 .095 no .Dlr'nc 1 f (.01?) WEE mm] ( J n = 2125, a? = {1036 Interpret the coefficient on pcrru. as well as the intercept. Q2 b (4 points) We then add the information on the total time spent in prison, as well as the number of months spent in prison that year and get the follow results: nfarr = .357 +.002tottime - .093penv - .0016inc - .0132ptime (2) (.017) (.002) (.027) (.0001) (.0059) n = 2725, R2 = 0.0381 Interpret the coefficient on ptime, and test whether the effect of ptime is significant at 2% 5% and 10%. Make sure you specify your test statistic, explain how it is calculated and distributed, and how you reach a conclusion about your test.Q2 c (3 points) Test whether the effects of fortime and prime are jointly significant at the 1% level. Calculate your test statistic, indicate how it is distributed, and explain how you reach a conclusion about your test. - 1 + Drag and drop an image or PDF file or click to browse