Question 5: A scientist is analyzing some recycling weight data and wishes to construct a bootstrap T confidence interval since he is not sure the population of all recycling weights is roughly normal (and he's not sure if the sample size n14 is large enough for the CLT to make "W-bar" approximately Normal.) The scientist generates a vector of 5000 "t-haff values using the bootstrap() function code from lecture and the 14 recycling weight values he collected and saves it to Recycling.boot. He then runs the following code: quantile(Recycling.boot, 0.025, 0.05, 0.10, 0.90, 0.95, 0.975, 0.99))) and gets the results: (common. quants=quantile (Recycling. boot, 01, 0.025, 0.05, 0.10, 0.90, 95% 97.5% 1.612953 1.932285 0.95, 0.975, 0.99))) 2.5% 5% 10% -3.085931 -2.433921 -1.970842 -1.513956 1.231860 2.310086 What bootstrap t multiplier(s) should the scientist use to make a bootstrap-t 95% Cl to follow the procedure outlined in class? C) t.lower- --1.97, t.upper=1.613 C) t.lower- --2.43, t.upper=1.932 C) t.lower=-1.96, t.upper=1.96 C) t.lower- --1.613, t.upper=1.613