 Hi everyone it's MJ and welcome to this introductory video to the course on conditional expectations. Now in the previous course we saw that sometimes we can have multiple random variables that contribute to our data. What we're going to be doing in this course is extending that idea and we're going to be extending it by looking a lot more into probability and generating functions. So the generating functions come to help us with something called a compound distribution whereas the probability is going to help us with our conditional distributions. And I mean conditional distributions this is very much of the situation where you know what is the variance of y given x and writing that out in terms of y and x where these two things are random variables. We're also looking at this thing called the compound distribution which is used a lot in insurance and the general idea is that as an insurance company you have two random variables that contribute to your total claims and the one is the number of claims you know do 10 people claim do 100 people claim how many people are going to claim and then each of those claims is going to be its own random amount you know if you're doing household insurance every person who makes a claim their amount is going to be different it's going to be a random variable and the number as well these things are going to have unique parameters and unique distributions that need to be combined to form a compound distribution and generating functions are once again going to come and save the day they're going to help us avoid having to use calculus and with conditional distributions we're going to see a lot more of the probability theory that we use being applied and once again this can then help us when it comes to answering questions in the insurance industry. So that is a very very brief introduction to conditional expectations we're looking at you know what's going to be the mean and the variance of them we're also looking at compound distributions and how we can apply the moment generating functions to this material but i'll see you guys in the course and i'm looking forward to this one keep well cheers