20 babies born in one week in a local hospital had the following weights (in pounds): 9.6, 8.8, 5.1, 7.7, 6.1, 8.9, 8, 9.2, 5.7, 9.1, 8.5, 7.3, 9.3, 9.6, 5.2, 9.9, 7.6, 9, 7.2, 8.5(a) create a qq plot and histogram of the weights. do you think it is reasonable to assume that thepopulation distribution is normal? explain your answer.(b) regardless of your answer to (a), use r to perform the bootstrap with 3000 resamplings (and set. seed(1))to create a 98% ci for μ. (show your r code and its output - you can copy and paste the code given in lecture or ) now construct a 98% t ci for μ by hand and compare it to that which you found via bootstrap.(d) last year, an oil refinery was built in the vicinity of the hospital. the average of newborn baby weightsthe previous year was 8.4 lbs. using the data from this week’s births, use the bootstrap with 3000resamplings to test the hypothesis that baby weights are lower after the refinery started operation (set α = .02. make sure to specify your null and alternative hypothesis, report p values, and draw your conclusions in context.(e) do the same hypothesis test with a t instead of a bootstrap. use an online calculator if necessary.