Information about a sample is given. Use the information to compute and interpret an interval estimate. What is the parameter being estimated. Use a 95% confidence level. [Hint: see notes on first page.] The sample proportion of students in favor of free drinks at hockey games is 32% (=0.32) and has a standard error is 0.04.

The parameter being estimated is the proportion of the entire population of students in favor of free drinks at hockey games.

The 95% confidence interval for the proportion of students in favor of free drinks at hockey games is between 0.28 and 0.36.

This means that we are 95% sure that the true proportion of the entire population of students in favor of free drinks at hockey games is between 0.28 and 0.36.

Step-by-step explanation:

The sample proportion of students in favor of free drinks at hockey games is 32% (=0.32) and has a standard error is 0.04.

Initially, this means that the parameter being estimated is the proportion of the entire population of students in favor of free drinks at hockey games. We build a confidence interval from a sample, and estimate for the entire population.

Confidence interval

Has two bounds, the lower bound and the upper bound.

Lower bound is the sample proportion subtracted by the standard error. So 0.32 - 0.04 = 0.28.

Upper bound is the sample proportion added to the standard error. So 0.32 + 0.04 = 0.36

The 95% confidence interval for the proportion of students in favor of free drinks at hockey games is between 0.28 and 0.36.

This means that we are 95% sure that the true proportion of the entire population of students in favor of free drinks at hockey games is between 0.28 and 0.36.