 Hi everyone, it's MJ and welcome to the introductory video for the course on regression. Now regression is one of the big, big areas in statistics. It allows us to create these things known as models, which are phenomenal when it comes to answering questions and a whole bunch of things from insurance, financial markets, scientific research, a lot of things use the concept of a model. What we're doing in this course though is we're just looking at something known as linear regression. So it's very much baby steps and it can come across as a little bit too easy. But what we're going to be doing in this course is we're going to be introducing a lot more of the jargon or a lot more of the areas when it comes to models. This is stuff such as correlation. We're going to be looking at something called residuals and we even touch on a very, very interesting area known as transformation. So we touch on these things. We don't really go into a lot of detail and the linear model is very simple. But what it does is it creates the foundation for those of you who want to take stats further and create more complicated models. It really gives you a solid understanding of where everything comes from. So it is quite an easy course. It is quite an easy section. But don't underestimate it because sometimes the theory can be a little bit tricky, especially when we start adding on multiple regression and all those things, which you will come across in later stats courses. Anyway, if you've got any questions, feel free to ask me in the comment section below, but I look forward to introducing such a powerful component of statistics to you. Enjoy. Cheers.