You are interested in the length of time of a typical cross-country race. You randomly sample a group of 20 races and come up with the following race lengths (in minutes). The lengths have been sorted for your convenience: 12, 139, 175, 175, 178, 184, 187, 188, 188, 192, 192, 200, 202, 205, 206, 207, 209, 211, 233, 24 1. Before embarking on the numeric analysis, examine the data. Decide whether or not there are any outliers in the data. Because this is a very small dataset, you can simply look over the values. However, a graph such as a boxplot or histogram is an even easier way to quick! identify outliers. (And with larger datasets you will not realistically be able to look at all of them, so you will have to plot the data). However, for now, simply look at them without graphing. Now proceed with the following statistical analysis: 2. Provide the 5-number summary. Do this manually, that is, do not use R. 3. Using the 1.5 IQR rule, indicate which races, if any would be outliers on the high side. A Using the 15 JOR nule indicate which races if any would be outliers on the low side