 Hi, this is Dr. Don. I want to take a few minutes and explore with you how StatCrunch creates blocks plots in the new version of StatCrunch. It's a little bit different, and some students have been tripping up on it, so I'm going to walk through to show you how you can answer a question like this. And we're given a data set, and we're asked to find the five number summary, and then also to pick the right box plot. Now these are drawn horizontally, which is something we can do in StatCrunch. What I'd like you to do when you look for the right answer, and of course here's the correct answer, click on this little icon there to open it up so you can inspect these box plots a little bit better. One of the important things I like to look at is what is the minimum value that is on the x-axis and what is the max value? And here it goes from two to nine, and we'll use that when we set up our box plot. In StatCrunch, and looking at all of these, they all seem to go, the minimum value on the x-axis is two, and the max value is this little blip there, which is nine, same there, same there, same there. So I'll use that when we get into StatCrunch. And we do that again by just clicking on the icon and opening the data in StatCrunch. Okay, I have the data in StatCrunch, and to get the box plot that we go to graph, box plot. We need to select our data column, which is variable one, I didn't rename it. And now this is the part you need to pay attention to down here. We have options. And notice that the default for StatCrunch when it opens is to use fences to identify outliers. Now, that is what will confuse some students. So what I like to do basically is to uncheck that. So we just have a basic box plot, and then check on draw box plots horizontally. If your question asks you to find outliers, then you could use that and leave it checked. All right, so we hit compute, and we get our basic box plot. And what I like to do again, because these are usually pretty skinny in the choices. So I make that look like, and I double check to see what are the max and min on my x-axis. And I can see that and change it if necessary by clicking here. You can see that it does default, particularly well here to the minimum of two and the max of nine, which matches our options. So I'm gonna leave that okay. So to get our five number summary, we just hover, and there we get the IQR, which this problem doesn't ask us to do, but some might, and it gives you the min value, Q1, the median, the 50th percentile, or Q2, Q3, and the max value. So that's pretty straightforward. Let's see what happens if I leave that box checked to identify outliers. We're gonna click options, edit, go back and click that this time, and compute. Now here, we get the same result, and if we hover though, we see that the naming convention has changed a bit. Instead of minimum, it says lower limit, and instead of maximum, it says upper limit, but that might still be understandable. So we're okay here as long as we don't have an outliers. So let me add an outlier and show you what happens and why this recognition of checking that box not makes a difference. I'm going to go back here to my data, and I wanna add another data point, 20, which would be an outlier, I think, for these data. Let me go back to options, edit, and then compute. Now here, with that box checked, you can see that the presentation totally changes, and so you would have a hard time matching it to your answer options. And it does identify that you've got one outlier there, and it doesn't tell you which it is, which you can pretty well hover over it. You can see the value is 20, but the rest of the box plot doesn't look right. And we go back and change that option, uncheck that, and click compute. Then our axis has changed a bit, because we now have that 20 in there, but if we hover, you can see you're back to giving the max and the min. So just be aware of that when you're working with that. Check that box if you need to identify outliers. If not, I suggest unchecking the box. Hope this helps.