 Hi folks, this is Dr. Don. Let's take a few minutes and walk through the Lab 6 remix. We've had some questions about it and some people are uncertain how to proceed. So I'm going to just kind of take you briefly through what you need to do. Here is the Lab 6 remix that we had to written up. And of course everything else at the top you're probably pretty familiar with. Let's go on down here. Remember always load the libraries, load the data if you've got that. And here we're given a choice that we need to answer one of these two research questions. So the first one is, is there a difference in total SAT score for students with a low and a high school GPA? Okay, now that's reminiscent of one of the examples in Lab 6 in which we're comparing the means. These would be quantitative variables, high school GPA, high and low. And since we've got a group of students here, we'd be comparing the means. That sounds familiar, one of the examples. The other question is, are the mean, math, verbal and total SAT scores different for the students? Now this doesn't have a categorical variable like the high school, high and low GPA. But we've got three quantitative variables. So that would be the ANOVA, another example in the second rehearse in Lab 6. Most students I feel, and in my experience of being, will choose the first one. It seems to be the friendliest, but let me tell you, the ANOVA is just as easy. And you can pick that as well and follow the example. But let's go ahead and scan down here. The first thing that we're telling you is that you're going to have to insert your own R chunks. And that's all you've got to do there is find the little green square with a plus, click on that and insert R. And that'll give you a blank code chub that you can work with. You'll probably also have to do some typing just like you would with a term paper. And remember in R Markdown we can type pretty much just like we would with Word or some other word processing program. So the first step it says, read in the data, always got to get the data in just like we always load libraries. And it says save to a local data folder. And if you don't remember how to do that, you can go up here to code chunks and there's a look at one of the code chunks. It'll show you an example of how to save to the local folder. Always, you know, state clearly what your research question is, the one you're choosing. Always begin by stating in words the null hypothesis and the ultimate hypothesis. One thing I don't mention here, but you should always do when you're doing research. Before you do anything else, you should also set your significance level, your alpha. And traditionally we'll use the 0.05, which is 5%. We don't want to be wrong more than 5% of the time. So that would be the significance level as you should set as well. And then it says to follow the downy in for a process and gives you the steps there, the growth steps that you could go through and follow that. And then down the bottom it says remember to always begin by exploring the data. Always state the null alternative. We mentioned that and include a visualization. So we're going to do question one. And that comes from the example is in lab six. Rehears one. So I'm going to click over there to that. And here is one sample, one mean. We've got two samples, two mean. So I'm going to click down here at the bottom. And it's got a similar question. Here our categorical variable is the identified sex, males and females, first year GPA, different variable for us to use. But this takes you through the steps. And what I would do would just be to type this in pretty much into your worksheet and then load these, you know, follow these code chunks. And you'll probably need to use, you know, all those. We've already loaded the sat GPA. But then we're creating a version of that data object. And then we're starting to go through the input process. This first one is specify the step. Excuse me, specify the relationship between the two variables. And then just follow down these code chunks. Insert the blank ones where you need them. Type in something if you need to add something to tell you where to go and follow through these things. Now, you don't have to answer all the reflection questions. You can just ignore those in your exam or you can answer them for your question if you want, but it's not required. Just follow through these steps. And that's pretty straightforward. And then when you finish up, you won't have the graph, of course, you'll calculate the p-value. You'll compare the p-value to your alpha level of 0.05. And then that'll tell you whether or not to reject the null. We want to look at a confidence interval, another way of doing a hypothesis test to see if our null value is in the interval. And then we're going to do the theoretical. Remember, we normally have to test the assumptions for the theoretical. But that's really all you've got to do. Of course, state your conclusions. What did you find? What is the result of your analysis?