A travel company is investigating whether the average cost of a hotel stay in a certain city has increased over the past year. The company recorded the cost of a one-night stay for a Friday night in January of the current year and in the previous year for 31 hotels selected at random. The difference in cost (current year minus previous year) was calculated for each hotel.

Which of the following is the appropriate test for the company's investigation?

a) A one-sample z-test for a population mean

b) A one-sample t-test for a sample mean

c) A one-sample z-test for a population proportion

d) A matched-pairs t-test for a mean difference

e) A two-sample t-test for a difference between means

Question

Cordell Grimes

Mathematics

10 May, 00:58

A travel company is investigating whether the average cost of a hotel stay in a certain city has increased over the past year. The company recorded the cost of a one-night stay for a Friday night in January of the current year and in the previous year for 31 hotels selected at random. The difference in cost (current year minus previous year) was calculated for each hotel.

Which of the following is the appropriate test for the company's investigation?

a) A one-sample z-test for a population mean

b) A one-sample t-test for a sample mean

c) A one-sample z-test for a population proportion

d) A matched-pairs t-test for a mean difference

e) A two-sample t-test for a difference between means

+5

Answers (1)

Know the Answer?

Kaleigh Fischer · Answer 1

d) A matched-pairs t-test for a mean difference

Step-by-step explanation:

The appropriate test for the company's investigation is a matched-pairs t-test for a mean difference.

A matched-pairs t-test is a test that is used to test if compared datasets have significant mean difference.

In this case, the travel company wants to compare the cost for the month of January of the present year, and the cost for the month of January of the previous year for different hotels selected at random.

The travel company also takes the difference in cost of all samples.