So now we talk about one of my favorite topics hypothesis testing. And the reason why I love this topic is because it's really about decision making. We talked a lot about data or often called the sample and we used statistics to extract information and now we use more statistics to make decisions and the decisions to be binary, be it a yes or no. And the reason why I like this, I think life is all about decision making. I think there is no meaning in doing statistics without eventually at least making a decision.
This is the first time in this class, you're going to make an actual decision. So in this box of pills for weight loss and particularly it says that 90% probability, taking these pills, a substantial weight loss is being guaranteed. Now suppose your job is not to make a decision whether to buy this box or not. I can promise you in all likelihood why those pills don't work but whether this claim is correct or not so you really care about why the company that sells this product made a correct thing. And to do so, you talk to people who have taken this medicine and you ask question–did you lose weight? Yes or no and say this is a magical medication.
And 11 out of 15 people tell you yes, but 4 out 15 people tell you no. Obviously, this is not 90%. In fact, what do you think it is in percent?.