 Again, due to popular demand, I've made some templates for your research question reports. This will make it a little bit easier to give you a structure that's based around the Downey Infra Method, but it can be used for either of the methods of doing hypothesis testing. If you haven't already set up your Lab 7, then these templates will be automatically in there, but for those of you who already have your Lab 7 set up, I will have copies of these templates, an announcement in the course, and also I'll put it in the tips and tricks, so that you can, several ways you can get copies of these templates. Well, let's walk through the template. There's Label Research Template Q1, Research Template Q2, one for each one of your research questions. Again, if you've already done Lab 7 remixed, don't worry about it. You know, however you approach it is probably okay. This is just something I thought would help students that are struggling a bit with structure, and maybe future students that will help a little bit too. But anyway, you would put your name and the date in there, and then as you scroll down, we've got the standards loading of the packages into the library, and then a reminder on Downey's 5 Infra Steps, and then we've got a number of initial steps that you would use for whatever research question. The first one is state your research question and the problem. So I'm just going to go back here and copy this out of my remix. Here's my Research Question 1. I'm going to copy that all the way down to the actual question. Control C, go back here, and then put my Control V. So there, I've got my research question stated, and that's where you would start to do. The next thing you do is state the null and the alternative. You just put your cursor there and write it out what the null hypothesis should be. Always a form of no difference. There's nothing going on, and the alternative, which is the flip side of the null. And then mistake the significance level. I'm just going to ahead and put it in there. Most of you would use .05 anyway, and that's pretty much the default. So that's in there for you. And then you get familiar with the data. The first thing is to load the data, read in, and inspect the data. Now I've added examples. Remember the little pound sign allows me to comment out code, so R won't try to run that as a code, but I've just given you examples. And you may be able to edit this directly, or you may have to go back to your rehearse example. But this is more or less what it would look like if you were going to read in out of the data folder, which you would have to change the name of the file to the file you want to read in there. And then it's going that way. Inspect the data. I like to look at the head of the data file. And again, this example, you could take the pound sign off and then edit the name of your data frame you created. And that shows you the top. And then I like to look at the bottom using the tail function. Same thing. Just put in the name of your data frame there. And then when we're doing categorical data, I like to get the counts. And so this next example code finds the count. So that may not be needed for all of your research questions. But here's a section that you can use. And if you don't need it, just put not needed. And then finding the observed proportions, again, depending upon the format of your research question, you may not need that. For research question one, you do. And here's an example of how to do that. And all the way down, I've got the major steps for downing. And then example code that you would either have to copy and paste in your own code, or you might be able to edit this code that's already in there. That's your choice. And then I've given you place for comments on these things. In other words, once you run one of these things, you should have some comments. Why did you run it? What is it telling you? Okay. And then all the way down, calculate the statistics of interest, the delta, comment on what it equals, generate the null distribution, visualize the observed statistic in the null distribution. And then the comment on the visualization, give you an example of what that might be. And then calculate the p value. And then finally, state a conclusion. And here at the end, I've got the traditional method, an example of doing the thing with the traditional method, which of course, you would have to test all the assumptions for the traditional method. So that is your template, you would use one for question one, and then another for question two. And again, these are just optional. If you've already done the remix, don't worry about it. I'm sure whatever you've done will work just fine. But this should get you started.