The document discusses using bootstrapping to calculate confidence intervals without assuming normality of a population's distribution. It instructs the reader to add a line of code to ensure replicable random sampling. It then asks the reader to find critical t-values and the lower and upper limits of a 99% confidence interval created using bootstrapping versus assuming normality. The final question asks which method results in a wider confidence interval.

1. Your collaborators do not want to assume normality of the population. resamples. Add this line
of code at the top: It ensures that your sequence of random samples is the same as mine, so that
we will get the same answers. Find the smaller of the two critical t^ values, t^(1/2). Question 6
Find the larger of the two critical values, t^(0/2). Question 7 What is the lower limit of the 99%
confidence interval? Question 8 What is the upper limit of the 99% contidence interval?
Question 9 Which interval is wider: the one we get when assuming normality of the data, or the
one created using the bootstrap method? Bootstrap Assuming normality