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.
FourteenDays | NinetyDays |
202.09 | 234.19 |
361.69 | 326.39 |
114.29 | 132.59 |
267.09 | 270.19 |
207.09 | 205.09 |
185.29 | 129.49 |
931.99 | 947.29 |
156.99 | 121.29 |
493.99 | 667.69 |
93.69 | 95.39 |
182.29 | 184.59 |
303.69 | |
142.69 | 156.59 |
251.79 | 194.49 |
163.29 | 129.59 |
168.29 | 139.59 |
509.69 | 318.09 |
227.59 | 1242.09 |
122.29 | 113.99 |
283.29 | 146.59 |
597.59 | 378.09 |
330.99 | 306.39 |
273.59 | 226.99 |
121.79 | 114.59 |
267.09 | 270.19 |
781.09 | 793.79 |
123.69 | 87.49 |
146.89 | 104.19 |
123.49 | 86.39 |
233.09 | 265.19 |
106.29 | 107.59 |
251.79 | 194.49 |
227.29 | 230.09 |
169.29 | 96.19 |
178.79 | 138.69 |
263.09 | |
254.29 | 192.59 |
189.29 | 106.59 |
148.29 | 106.59 |
131.29 | 109.59 |
196.39 | 183.09 |
199.39 | 123.69 |
254.29 | 143.59 |
224.79 | 199.69 |
284.69 | 184.59 |
395.39 | 326.39 |
179.29 | 118.59 |
259.39 | 263.09 |
299.19 | 210.09 |
168.29 | 170.59 |
211.09 | 164.59 |
175.29 | 150.59 |
259.39 | 183.09 |
215.29 | 129.59 |
285.79 | 194.49 |
229.29 | 164.59 |
306.79 | 230.69 |
100.59 | 72.29 |
186.79 | 188.69 |
102.19 | 148.89 |
396.19 | 298.49 |
123.29 | 106.59 |
215.29 | 136.59 |
362.79 | 250.29 |
1158.69 | 1176.99 |
171.29 | 131.59 |
453.19 | 281.09 |
349.29 | 286.99 |
151.29 | 114.59 |
140.29 | 104.59 |
312.24 | 721.34 |
284.69 | 188.59 |
309.99 | 210.89 |
172.29 | 175.59 |
365.49 | 296.19 |
285.79 | 330.49 |
770.99 | 782.09 |
334.49 | 121.59 |
255.29 | 120.59 |
149.89 | 124.19 |
284.39 | 240.09 |
261.69 | 180.59 |
310.89 | 194.89 |
350.69 | 354.69 |
251.79 | 194.49 |
205.29 | 283.59 |
174.29 | 128.59 |
338.79 | 341.89 |
160.29 | 114.59 |
What is the P-value for this test? Round your answer to 3 decimal places.
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.
Hypothesis :
where is the population mean difference between the two variables .
Here we are given with the data of price of ticket of same flight on different days . So, we should conduct a paired t test .
We conduct the test using excel . The output from excel gives us the p value of the test .
Here is the snippet of the excel worksheet .
p value =0.132 ( rounded to three decimal places) .
As p value > alpha = 0.05 , the test fails to reject the null hypithesis .
In other words there is no significant difference in the price of the tickets at these given time periods.
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