a. By changing the number at the end of the command replace y_poor=y_bad if uniform() < 0.3, carry out the Monte Carlo separately for a grid of values of p ranging from 0 to 1. For each run, store the proportion of values of hausman2 that exceed 3.84 (i.e. store the power of the test, for each value of p assumed). Plot the power of test against p. Note that this is a plot of the power function of the test.