The number of undergraduates at Johns Hopkins University is approximately 2000, while the number at Ohio State University is app
roximately 40,000. A simple random sample of 50 undergraduates at Johns Hopkins University will be obtained to estimate the proportion of all Johns Hopkins students who feel that drinking is a problem among college students. A simple random sample of 50 undergraduates at Ohio State University will be obtained to estimate the proportion of all Ohio State students who feel that drinking is a problem among college students. What can we conclude about the sampling variability in the sample proportion, p with hat on top, calculated from the sample at Johns Hopkins as compared to that in the sample proportion from Ohio State
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Its ratio of samples by Johns Hopkins will be about the equivalent than those from Ohio State because sample varying depending on the sample, each of them would have the same variability also like the amount, that's why he assumes the variance of sample sizing in the sample percentage p with both the hat above, relative to the confidence interval in Ohio State determined from its Johns Hopkins test.
No, they are both incorrect by my understanding of your question use the Pythagorean theorem a^2 + b^2 =c^, therefore, 7^2 +x^2 = 13^2 or 49+x=169 then solve normally 169-49=120 √120 =5