JASP One-Way ANOVA Screencast

Okay. In this recording, I’m going to show you how to use JASP to complete a one way ANOVA. So here’s our data set and our dependent variable is pain tolerance. So it’s a pain tolerance score. I think it’s scored from zero to 100. So you’ll see our distribution of scores here in the third column. Our second column is then hair color, and we put hair color into four categories, light blonde, dark blonde, light brunette, dark brunette. I know this is a nonsensical example. We wouldn’t expect people’s pain tolerance to differ by hair color, but it’s a good illustration of how to use ANOVA. So I’m going to click on the ANOVA menu and drop down I’m going to pick ANOVA. I’m going to choose my independent variable or excuse me, my dependent variable. Move that over and then move over. Let’s get rid of this. I’m sorry. These are my old results.

So let’s start again. We’re going to go to ANOVA. We’re going to click in pain tolerance as my dependent variable. Hair color is my independent variable. And you see, we have significant. So we have significant main effects here or significant F score. So we need to run a post hoc test, it just tells us there’s a difference within the four groups. It doesn’t tell us specifically the nature of the difference. Do all four differ from each other or where exactly do the differences lie?

To do that, we need to run a post hoc test and it defaults to a Tukey, a standard Tukey, which we will do. We will select that. That works for us. We’re going to pick hair color and move it over. There’s our Tukey results. Before we interpret that, let’s go ahead and run descriptive plots, and I want to run them along the horizontal axis. And you’ll see since it smashes that bottom there, the horizontal axis. So if we go to the lower left, we can stretch it out and then it recalibrates. Now we can see the different types of hair colors. I’m going to move it back just a little bit. Too much.

Just move it back. Okay. So let’s see where our differences are. So we’re going to go up to the post hoc test. I’m going to scan this significance for anything below 0.05. So with dark blonde, there are no differences. All of those significance are above 0.05, but when I go to dark brunette, I see I have a difference between dark brunette and light blonde. So that’s this difference right here. And then when I go to light brunette, I see a difference between blonde and light brunette. So the difference is right here, okay? That light blonde is significantly high. They have significantly higher pain tolerances than both dark brunette and light brunette. So that would be a fair interpretation of that.