Now load the cats dataframe. 5. Find 95% confidence intervals for body weight and heart weight for male and female cats (ie, you will be finding four confidence intervals). Note that these samples are large enough that we don't have to worry about whether they are normally distributed. Include sentences interpreting your results. Based on your intervals, does there appear to be a significant difference between the heart weights of male cats versus female cats? How about body weights? 6. Go back to the Ten Mile Race dataframe and obtain 95% confidence intervals for the mean net race times for samples of size: a. 30 b. 230 c. 430 Include the commands you used, as well as sentences interpreting your conclusions. Notice that the number of simulations, or equivalently the sample sizes, differed by 200 from part a) to b) and again from part b) to c). However, although the confidence intervals shrunk with each sample increase (if they didn't, fix your code, because it means you did something wrong), they didn't shrink by as much the second time around. That is: although larger samples give tighter estimates, there's a point at which the improvement obtained by increasing the sample size isn't worth the extra work. This is why we seldom see samples larger than a few hundred.