[SOUND] In this video I'm going to show you how to compare population proportions from two different samples. Excel does not do a good job in doing this, so you have to do the calculations one by one. So what I have done is, I have created the worksheet which has been locked so you can't really edit it, but you can use it. So what I'm going to do is, go through the examples that we have in our PowerPoints and show you how I used that worksheet that I'm making available to you. When you're doing your own problems, you can just replace the input variables with whatever variable that you have, and then just know where to look for the answers in the worksheet. So let me show you a study that show that both girls and boys do equally well on math tests. A school district takes a random sample of 400 boys, and another random sample of 360 girls in grade 11, and looks at their most recent standardized test score. The math score of 315 of the boys and 280 of the girls were the proficient level. At 5% level of significance, can the school district claim that the boys and girls do equally well on math test? So if you look at this problem, what we are saying is that proportion of girls who do well on the test is the same as the proportion of boys. Therefore, our null-hypothesis is that proportion of girls who will do as well as boys, or they would get proficiency level, is the same as proportion of boys in the school. And the alternate is that this school have girls and boys do differently. So this will be a two tale test, right? Because we're doing an equal versus not equal. Let me show you how we would use the worksheet that I'm making available to you. So what you'll see in the worksheet when you open it up is an area that's highlighted in yellow. This is the place that you can enter your data. And the output will appear here. And because I have nothing right now here everything in the output section looks like [INAUDIBLE] error message. That will be fixed as soon as you enter values. So, let's say my sample one is going to be my sample of boys that are in the school took the test. And it says, Count of events. These are the boys who performed at the proficient level. And based on the our problem, there were 315 of them. And we looked at 400 boys. Count of events in sample 2, here sample 2 would be the girls. And based on the statement we had is that 280 of these girls did proficiently well in the exam out of the 360 that we have looked at. And level of significance here is 0.05. And the hypothesized difference here is that they're the same, they're no different. So it's 0. So what you will see is that this started getting populated. First of all, it says that 78.75% of the boys did proficiently on the exam. 77.78% of the girls did proficiently on the exam. And the difference you see, is right here, which means the difference between the two is 0.97%. But again, we have to make sure that this is significant or not. So, as you have seen in Excel itself, my worksheet also will return everything to you. That means it will do a one-tail test on a two-tail test. You have to pick where your answer is. So, let me go down and show you what you will see. So here's our complete data. So I am going to focus only on this part, the bottom part, of the table because this refers to the two-tail test. And looking at the p-Value right here, you that it's greater than .05. So you end up not rejecting the null-hypothesis. And the non-hypothesis was that boys and girls will do equally well, so we are not rejecting this.