 Hi everyone, it's MJ and welcome to this introductory video on exploratory data analysis. Now this is the very first course, which means this picture over here is probably the first time that you are seeing it, in which case it can be a little bit overwhelming, you're like, whoa, look at all this crazy stuff that's happening. But in a nutshell, what is happening is that we have some data, we do some stats, we get some information about the parameters and distributions of this thing called the random variable, which generated the data. And once we know that we can answer questions and optimize processes, that is statistics. Now what we're going to be doing in course one is we're going to be looking at this link of going from data to statistics. And we're going to be using two forms of very basic maths known as graphs and algebra. The graphs are a great way for us to try and figure out what the distribution is going to be. And the algebra is going to help us to calculate something known as the mean, which is a statistic that is very good at estimating the parameters. And this is where the algebra comes in. So we're using graphs for the distributions and algebra for the parameters. And these are very important because once we know them, we can then push forward for these higher things like answering questions and optimizing processes. Now this course is going to be probably the easiest of all of them. Don't let it fool you that the rest of the stats is easy. It's not stats is difficult. However, this is an important course. And I mean, a little fun fact is that what we would see when we come to the central limit theorem is that how statisticians initially got this idea was using simple graphs. It would take them another 200 years for them to prove this idea using proper mathematics. But graphs did give them the initial idea, which allowed statistics to really blossom as a subject. So I hope you guys enjoy the course and that this puts it in the big frame of mind of what you're doing and why you're doing it. And yeah, if there's any questions, please feel free to ask them in the comment section below. See you for the rest of the course. Cheers.