Question

Members at a popular fitness club currently pay a $40 per month membership fee. The owner of the club wants to raise the fee to $50 but is concerned that some members will leave the gym if the fee increases. To investigate, the owner plans to survey a random sample of the club members and construct a 95% confidence interval for the proportion of all members who would quit if the fee was raised to $50.

(a) Explain the meaning of "95% confidence" in the context of the study.

(b) After the owner conducted the survey, he calculated the confidence interval to be 0.18 0.075 Interpret this interval in the context of the study.

(c) According to the club's accountant, the fee increase will be worthwhile if fewer than 20% of the members quit. According to the interval from part (b), can the owner be confident that the fee increase will be worthwhile? Explain.

(d) One of the conditions for calculating the confidence interval in part (b) is that and. Explain why it is necessary to check this condition.

Answer 1

Answer:(a) "95% confidence" means that if we were to repeat this study many times, we would expect the true proportion of members who would quit to be within the calculated interval for 95% of those studies. In other words, we can be 95% confident that the true proportion of members who would quit falls within the interval.

(b) The interval is [0.18, 0.075]. This means that we are 95% confident that the true proportion of members who would quit if the fee was raised to $50 falls between 0.18 and 0.075.

(c) No, the owner cannot be confident that the fee increase will be worthwhile because the interval from part (b) includes 20%. If the true proportion of members who would quit is 20%, then the fee increase would not be worthwhile. Since the interval includes 20%, we cannot be confident that the true proportion is less than 20%.

(d) One of the conditions for calculating the confidence interval is that the sample size is large enough and that the number of successes and failures in the sample are both at least 10. This is necessary because the interval calculation relies on the normal distribution, which is only valid when the sample size is large enough and the number of successes and failures are both at least 10. If this condition is not met, then the interval calculation may not be accurate or valid.

Explanation: