Use the data in LOANAPPRAW for this exercise- The binary variable to be explained is approve, which is equal to one if amortgage loan to an individual was approved. The key explanatory variable is white, a dummy variable equal to one iftheapplicant was white. The other applicants in the data set are black and HispanicTo test for discrimination in the mortgage loan market, a linear probability model can be used:approve = A, + filwhite + other fizctors.(i) If there is discrimination against minorities, and the appropriate factors have been controlled for, what is the sign of 81?(ii) Regress approve on white and report the results in the usual form- Interpret the coefficient on white. Is it statisticallysignificant? Is it practically large?(iin As controls, add the variables hrat, obrat, loanprc, unem, male, married, dep, sch, cosign, chist, pubrec, mortlatl, mortlatZ, and vr. What happens to the coefficient on white? Is there still evidence of discrimination against nonwhites?(iv) Now, allow the effect of race to interact with the variable measuring other obligations as a percentage of income(obrat). Is the interaction term significant?(v) Using the model from part (iv), what is the effect of being white on the probability of approval when obrat : 32, whichis roughly the mean value in the sample? Obtain a 95% confidence interval for this effect.