Q5 (15 points) Continuing the scenario from the previous question, let's look at Lucy and Lei's waiting time data: waiting.csv. Part (i) Run this code to load and to transform the data. Make sure the data file is in your working directory before you run the code. waiting % group_by (numberofminutes) %>% summarize (numberofcustomers = n()) zeroes % replace_na(list (numberofcustomers = 0)) What is the variable name for the Y;'s? What is the value of m? Part (ii) For the random sample Y,..., Y. it can be shown that Ho ~N (0, #) where it is the MLE from Question 4. Compute a 95% confidence interval for using this asymptotic distribution and the observed values of the random sample Y,..., Ym. Part (iii) Compute the likelihood ratio A based on the sample Y,..., Ym and evaluate the claim that = 2, that is, two customers enter the shop per minute. Is this claim supported by the data? Part (iv) Use a bootstrap procedure to estimate a p-value corresponding to the claim that = 2 based on Y,..., Ym. Is your value different than what you got in Part (iii)? Say why you would expect them to be the same OR explain why they are different.