 Hi everyone, it's MJ and this is the introductory video for the course on hypothesis testing. Now I love hypothesis testing and it's a very, very important component of statistics. In fact, hypothesis testing is where science and research and empirical investigations really gets involved and how it works, it's saying that, you know what, we need information on our parameter and our distribution. What would happen if we would have to set up a null and alternative hypothesis? Which is just fancy wording for saying let's take a guess of what we think the parameter is going to be and then let's look at the data, let's work out some confidence intervals and let's see if our guess is correct or not correct. So hypothesis testing, what we're going to be seeing in this course, it very much is a procedure, we've got a bunch of steps to follow, the math isn't that difficult, the philosophy behind it is interesting and we do discuss that in the course and it is something that a few students might struggle with, but other than that hypothesis testing it's a lovely, lovely part of the course because we're now getting to utilize a lot of the inference that we've been doing in the previous courses and we're actually using it now to answer some questions, to optimize processes and we're starting to see the fruit of statistics. So I'm looking forward to teaching you guys this course and as always if you've got any questions please let me know in the comment section below. Cheers.