So in this problem, we're gonna be looking at how out wires impact a scatter plot. I'm gonna be doing this in Excel. However, you need to do this in a graphing calculator. I will include the steps for that at the end. So first, we're gonna be making a scatter plot of the data. I'm gonna do free because later on in the problem, we're gonna need to separate the data into these three sections. The all right. So here is the data set and excel. I just highlight two columns go to insert, and then over here are the scatter quiets. So this is gonna be the one of all of them. The next one we want is without number 15. So to do that, I'm gonna highlight all of arm and hold control on Mac. It might be different, maybe, Commander, and then click on the two. We want to get rid of so the same thing again and start in your scattered quite. And I'll reach title this one without 15 a. So now I'm gonna make one without 18 on all title this one accordingly and next, we need to find the correlation for all three categories and then I'm gonna do the first part of part C at the same time, we're gonna make the regression line for all three categories of doing this and excel. We could just click on the crab if this plus fun in it. Check the trendline, barks and go to more options. And from there will put display equation on charts and display r squared on charts and I'll move those up here. So I'm just gonna go and do that with the over to now and trendline equation and r squared value if either too small to see all right them down at the end of China. So don't worry if you can't see you trendline more options equation and r squared. I don't now, don't this copy these down? This is our square that we don't want our squared. We want our The reason why R squared is called R squared is because it's literally just are square. So to get our all we have to dio is take the square root of r squared. So I'm gonna go back into a problem and I'll write down what we have so far. So our first equation put these in. Warrior Bar is equal to point or 82 and why is equal to 10 points or 08 x plus 66.4 to 9. So about 15 we get our is equal 2.568 and why is equal to 8.924 x, who s 69.487? Let about 18. We get our is equal 2.53 free and why is equal to 12 0.194 x plus 53.913 So let's take a look at the second half of part B. Do either of these outliers influence the correlation? Why did our change with these points? So as we're looking at these points, if you notice are seems to be higher without 15 18 however, it's not really that that big of a difference. So do either of these out wires influence the correlation. A little banza. It raises it a little bit. Now, why does it raise it a little bit? Well, without those out, wire points are graph is now able to be a lot more accurate at measuring all the other points, so any correlation we get is going to be much more accurate. So these two higher numbers are likely to be more accurate. So now we're going to make our regression line already did that. Do either of these outliers influence the lying? So we just take a look at them. We don't see a heavy amount of influencia. So again, the answer is a little bag. What we do see, though, is that the slope appears to be changing either up or down. Our default was 10 of the slope when we removed 15 it went down to about nine and then we were removed, 18 it up to about 12. So removing these out wires gave us a changing swell. So, for example, and this one we lost this high point out wire over here went away about 15 resulting in a lower slope because now the average point is a little bit lower. Whereas in this bottom graph, it went up a little bit because that point far off to the right as it is on the lower half. So removing it raised Arsal ova. So that looks like that's everything you need for this line. Here are the calculator steps to do this, you could take a screenshot off this, that this will explain how to enter data into your calculator, how to make a scatter plot to get r and r squared. And this is a one time setting. So if you've already done this, you can skip this and then finally, how to make the regression equation, which will have our in our square. And there are some pictures to help you do that, too. If you aren't using a T I calculator, most books will usually have a tutorial on how to do stuff like this for various different calculators. So you might be able to find these steps in your textbook till, and I think we're going.