 In our last chapter on the t test, we looked at methods that allow you to compare two things at a time two groups where you're looking at the mean differences between them. But what if you have more than two things you want to compare or maybe you even have a whole bunch of different groups that you want to compare. And you're trying to get insight into how those groups differ and how they affect the outcomes that you're interested in. Well, in that case, you're going to want to use the analysis of variance, also called ANOVA or ANOVA. And in this chapter, we're going to look at a few variations on the ANOVA theme that Jamovi makes available to us. The first is the standard factorial ANOVA. This is where you're looking at how one factor a categorical variable that splits people into different groups influences your quantitative or continuous outcome variable. You may have one factor you may have several factors simultaneously. We'll also look at the repeated measures analysis of variance where you're looking at people across more than one measurement time. Then we get into some things that really are rather sophisticated the analysis of covariance and COVA, and the multivariate analysis of covariance where you have several outcome variables, and you have some quantitative variables you're putting into the equation as well. It's an amazing thing that Jamovi makes these available and it makes them easy to work with. And then finally, we'll look at a couple variations on non parametric analysis of variance, where instead of making analyses based on means and standard deviations, we're looking at ranks and taken together all of these variations on the analysis of variance, give you a much broader range of situations that you can analyze and a lot more potential for getting insight out of your data. And so let's take a closer look at the analysis of variance.