Hi, my name is Brian and welcome to the class Advanced Linear Models for Data Science 2. In this class we're going to build on the material that we learned in Advanced Linear Models for Data Science 1. You really need to know that material quite well before moving onto this material. So if you feel a little bit fuzzy on it or you haven't taken it for a while, go back and review that material, it's all also on YouTube if you don't want to re-enroll in a Coursera course. In addition, in this class we're going to really focus on sort of the theoretical underpinnings of linear models and this will help you be a better applier of linear models. But we're still not going to spend that much time going over the application. So in order to augment this, it would be useful to also look at my regression models course on Coursera. I've included a lot of the links in the readings before the lectures start where you can go and watch the relevant regression model and lectures. What we'll go over the important applied topics that coincide with the theoretical topics that we're going to be discussing in this class. So make sure you watch those lectures if you aren't already familiar with that content. In addition, I'm going to presume that you have a basic working understanding of mathematical statistics, and when some of those concepts are needed, and you may or may not have had them, I'll include some links to my course Mathematical Biostatistics Boot Camp 1 and 2. Which covers some of the univariate basics that we'll need to cover the multi varied versions for this class. So in this class, mostly we're going to be focusing on are the distribution of results associated with linear models where we assume normality with spherical or IID normal airs with maybe a common variance. So we're going to show how we arrived at f test and high score testing, t test that are associated with this model. Again, it'll be a fairly theoretical treatment. But when we can, if we could tie it to how we think about applications we're going to do that as well. So welcome to the class. I look forward to working with you and look forward also to seeing you in the next version of this class, Advanced Linear Models for Data Science 3. Which will hopefully be coming out soon.