 In this problem, we are going to find the equation of a regression line and then use that equation to predict some values. We're given a table of values that show calories, which is our independent or x-value variable, and sodium, which is our dependent or y-variable. We're going to do this using StatCrunch. I'm going to click on it. The first thing we're going to do is go to Stat, regression, simple linear, our x-variable calories, y-variable, sodium. We don't need to worry about the where group by. We're going to leave the hypothesis test checked. But here, we can speed things up a bit. We have a place where we can enter in the x-values for which we want to predict y. I'm just going to click in there. The first x is 160 comma 100. Go back over here. 130 and 50. 30 comma 50. Okay, we want to show the fitted line. And I think that's all we want to show. Yes, we're going to save the predictive values. And we're going to click on compute. Make this a little bigger. We have our first requirement, the regression equation. Y sodium is equal to 67.85, our y-intercept, plus 2.433 times the calories. So we'll just put that 2.423. And the intercept 67.853. Okay, now the graph, looking back over here on stat crunch, click the little arrow. And there's our graph. We've plotted the line. And we've got our data points. So let's look and see. It's got to be one of these two, since the only one's going up to the right. And I want to blow this up so I can see a little bit better. And there, if you look at it a little more closely, you can see that it's very similar to our graph over here, except of course the axes are truncated in the stat crunch view. So our first point is right about 250. And we've got two points that look like those two points, and so on. It looks like that one. So I'm going to say it's Charlie. And our predicted values, I'm going to go back here. The first one, the predicted value for 160 is 455.533. And our predicted value for 100 is 310. And the predicted value for 130 is 382. And a predicted value for 50. Well, although stat crunch gives us a value for 50, remember that we don't want to be predicting outside the data that we're basing the regression on. And our minimum value of x is 70. So 50 is outside of that range. And so really the prediction is not meaningful. I want to check the answer. And we got them all right.