4. Suppose we take a random sample of size n of Penn State University Park students, and ask each of them if they have been to a home football game. Define Y = # of students who answer “yes", i.e. the number of University Park students who have been to a home football game. We would like to estimate p, the proportion of all University Park students who have been to a home football game. Suppose p = 0.68, where p = Y/n. (a) Suppose n = 1,678. Construct a two-sided 95% confidence interval for p, the population proportion, using the first method for confidence intervals for p that we learned in class (on Jul 19).

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4. Suppose we take a random sample of size n of Penn State University Park students,
and ask each of them if they have been to a home football game. Define Y = #
of students who answer "yes", i.e. the number of University Park students who
have been to a home football game. We would like to estimate p, the proportion
of all University Park students who have been to a home football game. Suppose
p = 0.68, where p = Y/n.
(a) Suppose n = 1,678. Construct a two-sided 95% confidence interval for p, the
population proportion, using the first method for confidence intervals for p that
we learned in class (on Jul 19).
(b) Interpret your confidence interval from part (a).
(c) Now, suppose n = 51. Construct a lower one-sided 95% confidence interval for
p, the population proportion, based on the first method for confidence intervals
for p that we learned in class (on Jul 19).
(d) If n = 5 and n – Y = 2, then is the value of p, the Bayes estimator for p that
can serve as an alternative to p for small samples?
Transcribed Image Text:4. Suppose we take a random sample of size n of Penn State University Park students, and ask each of them if they have been to a home football game. Define Y = # of students who answer "yes", i.e. the number of University Park students who have been to a home football game. We would like to estimate p, the proportion of all University Park students who have been to a home football game. Suppose p = 0.68, where p = Y/n. (a) Suppose n = 1,678. Construct a two-sided 95% confidence interval for p, the population proportion, using the first method for confidence intervals for p that we learned in class (on Jul 19). (b) Interpret your confidence interval from part (a). (c) Now, suppose n = 51. Construct a lower one-sided 95% confidence interval for p, the population proportion, based on the first method for confidence intervals for p that we learned in class (on Jul 19). (d) If n = 5 and n – Y = 2, then is the value of p, the Bayes estimator for p that can serve as an alternative to p for small samples?
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