 Hi, this is Dr. Don. I have another problem out of chapter 10 about Chi-square. And then this one, I'm just gonna show you the steps of using stat crush, the technology and not get into the theory here. We're told that we have a coffee house. They've collected some data about preference among five brands. The sample was 200 customers. And it says calculate the Chi-square test statistic used to test the claim. This is one variable. We've got categories and we've got counts. And that tells me that say one way table or goodness of fit. We're gonna go to open and stat crunch. We've got our data there. We go to stat, goodness of fit, Chi-square. We need our observed, which is in our customers. That's the number of customers in each category. We don't have a column giving us the expected distribution, but we can say all cells are equal proportion. And we click compute and we get our answer there. Our Chi-square test statistic is 37.45. Those are our expected. There's our P value, which tells us that we have less than alpha 0.05. Therefore, we reject the null. But that's how fast you can do this using stat crunch for a one way table, goodness of fit. Hope this helps.