 Hi everyone, it's MJ, and we're looking at the introduction to the final course of phase one of statistics, which is on ANOVA. Now, what is ANOVA all about? And we see here that it's connected to this idea of optimizing processes. And ANOVA, it's very interesting because it stands for the analysis of the variance, but in a sense what we are trying to compare is the mean. So, some people get a little bit tricked up by that. You know, why are we comparing variances when we want to actually compare the mean? Because the ANOVA in a big way is an extension of some of the stuff we did in an earlier course. So in earlier course, we could compare two types of treatments. So when we could compare two types of treatments, we look at the stuff that we did in earlier courses. ANOVA, however, lets us compare multiple things, whether it be three, four, five, gosh, we could even compare 10 different things with ANOVA. And this is great when it comes to optimizing processes, especially around farming. That's where this course came from. There was a bunch of farms and they wanted to try out different types of fertilizers or different types of treatments. And they wanted to see which one was the best or if there was actually a difference between the various treatments. And that's where a lot of the maths came from. It came from trying to improve farming. And it was very, very successful. And it is something that a lot of people at the PhD level or a lot of research, or if you're doing your masters or a thesis or something like that, you might very well come across ANOVA. And there's a lot of stuff on the internet telling you how to do ANOVA. But what you're going to learn in this course is you're going to understand why you use ANOVA, where does it come from, and why are we looking at variants when we're actually trying to compare the means. So it's a lovely course. It's a lovely section. It's not that difficult once you get your head over it. But yeah, I think it's a nice way to end off phase one of statistics which deals with this as the big picture. Anyway, if you've got any more questions, please let me know. Otherwise, I'll see you in the course. Keep well. Cheers.