 Now that we have our variables, now we can identify our experimental groups. We can identify the groups that are going to receive treatments in our experiments. We can identify the groups that are going to have the independent variable manipulated amongst them. I think of those as experimental groups, but really the whole, I mean, I'm including one of the, okay, focus. Experimental groups. And this is a group of subjects that receive treatment in some way, shape, or form. And then you have a control group. And the control group does not receive treatment. And as those words are coming out of my mouth, I realize that this little scenario that we set up, we have to almost define, like, who would be the control in this scenario? Everybody's either getting protein or not getting protein, or some, like, range. Maybe we say our control group gets no protein whatsoever. I mean, we could, the concept of a control group becomes a little bit fuzzier in this scenario. Some experiments have a really clean, nice, easy control group. Let's find out if light helps plants grow. Let's just not expose some plants to light and see what happens. That's your control group. The experimental group gets different amounts of light. Okay, so sometimes, not always, but sometimes you have two different flavors of control groups. And so you can have a positive control and you can have a negative control. And this, we're going to play with this for the entire semester. So a positive control shows expected results. And what that means is you actually are testing to make sure that your experimental design can show results. So a positive control in our diet scenario, which I think our diet experiment has broken down and become very poor, a positive control would guarantee results to show that people who eat actually can, people who gain weight, actually that will be detected by your setup for measuring weight, which is your scale. So feed them like 5 million calories, I'll be in that group and I'll eat 32 pints of Ben and Jerry's every day to show you that your scale actually works when I turn into a balloon. That's a positive control. We're going to show you the results that you're expecting to see. A negative control does not show you results. In fact, it's no results. And that, an example of a negative control is my light situation. Or I suppose we could starve someone and then we definitely wouldn't, well, that's a terrible example. Let's not even use that one. But if we don't show light to, or if we don't give a plant light, it's not going to grow. And if it's not growing, then we're not getting results. We know that it's possible for our experiment. Our experimental design is not going to show us false positives because we've done this negative control to show that, yeah, we actually, it's possible to get no results. Did you understand that? It's a little bit weird to think about. But we're going to have a couple of really good examples as we proceed through the course and we will remember to bring this back and talk about it then. Okay, let's look at what happens with our data after we've got our groups and now we're going to run the experiment and collect some data.