This question will be perfomed entirely in R. Consider thefollowing sample from an unkown distribution:
sample_data <- c(1.15, 0.5, 28.03 , 0.085, 1.82, 25.30, 0.7,0.02, 0.01 ,13.23)
1.a) Calculating the p-value using the bootstrap hypothesistesting method to determine whether the mean is greater than 1(one-sided test). Use 10,000 bootstrap samples. Set the seed to 248before beginning the bootstrap process, i.e. include this line ofcode at the beginning of your script.
set.seed(248)
Include a histogram of the generated bootstrap samples of X??, doesit appear to be symmetric? Do you
reject the null at 0.05 significance level? (10 points)
1.b) Find the rejection region (for X?) based on your bootstrapsamples at a 0.05 significance level. (5 points)
1.c) Perform a t-test for the same hypothesis as in 1.a) usingthe t.test function in R. Make sure that you apply the correctarguments.
Do you reject the null at a 0.05 significance level based on thet-test?
Compare the p-value from 1.a) to the p-value from the t-test, dothey imply different conlcusion? Which p-value would you trustmore? Support your anwser. (10 points)
