 This is the video on two sample hypothesis testing, comparing two proportions. You wish to test the following claim, the alternative hypothesis, at a significant level of alpha equals 0.01. So it's important to note that my claim in this case is the alternative hypothesis, and the sign is less than. You obtain 67% successes in a sample size of N1 equals 800 from the first population, and you obtain 73% successes in a sample size of 300 from the second population. I want you to find the test statistic and the p-value, and then we'll come to a conclusion on the hypothesis test. For Google Sheets, I need to know the number of successes and the sample size for each group. Group one is the group on the left of the subscript of one, group two is the group on the right of the subscript of two. They gave you the percentage successes, then the number of successes, which is x, is equal to the sample size times the percent of successes. That's how you find the number of successes. So in this case, x1 is 800 times 0.67. That's 67% as a decimal. That gives me 536. My sample size for group one is 800. The number of successes for group two would be 300 times 0.73. That's 219. The sample size for group two would be 300. And take note that my alternative hypothesis has a sign of less than. These are the five pieces of information I need to plug into Google Sheets. So in Google Sheets, we'll go to the data list tab. We'll go to the two prop CLP value region. Type in successes and the sample size for group one. That would be 536, 800. The successes for group two, 219, and the sample size 300. And make sure you change your hypothesis sign to less than. And it looks like we have a test statistic of negative 1.91 and a p-value of 0.0281. That's the information that we need. So the test statistic would be negative 1.91. The p-value will be 0.0281. Now let's compare the p-value to alpha, which is 0.01 in this case. Keep in mind your claim was the alternative hypothesis here. Our p-value is being compared to alpha. In this case, the p-value of 0.0281 is greater than 0.01. As a result, we fail to reject the null hypothesis. So looking at our summary statement table, we failed to reject the null hypothesis and our claim does not include any quality, which puts us in row three. So this is the general format of our statement. So our statement is that there is not sufficient evidence to support the claim that the first population proportion is less than the second population proportion.