Answer:
C, B, 0.096, C
Step-by-step explanation:
Here is the complete question and answers
Pressures of supply and demand act directly on the prices of airline tickets. As the seats available on the plane begin to fill, airlines raise the price. If seats on a flight do not sell well, an airline may discount the tickets or even cancel the flight. Allie Henrich, a BYU-Idaho student, wanted to determine if there is a difference in the price of tickets listed 90 days before a flight compared with 14 days before the same flight. For her study she compared the prices of one-way flights from London's Heathrow Airport to various destinations in Europe. Using Travelocity.com, she recorded the lowest published fares for 90 nonstop midweek flights 90 days in advance and then found the lowest published price for the same destination again 14 days in advance. The prices (in US dollars) are given in the file DirectFlightCosts.sav. Notice that for some destinations, flights were not available.
Question 1
Which hypothesis test would be most appropriate for this study?
A One sample z-test
B One sample t-test
C Paired-samples t-test
D Two sample t-test
Answer: C
Question 2
Is the alternative hypothesis for this test one-tailed or two-tailed?
A. One-tailed
B. Two-tailed
Answer: B
Question 3
What is the P-value for this test? Round your answer to 3 decimal places. (Example: 0.045)
Answer:
0.096
Question 4
Based on the results of the test, can you say that there is a difference in the cost of airline tickets purchased 90 days in advance compared with 14 days in advance? Use a level of significance of α=0.05 {"version":"1.1","math":"\alpha = 0.05"}.
A. Yes, because the P-value was greater than the level of significance.
B. Yes, because the P-value was lower than the level of significance.
C. No, because the P-value was greater than the level of significance.
D. No, because the P-value was lower than the level of significance.
Answer: C
