In: Statistics and Probability
It has been suggested that the highest priority of retirees is travel. Thus, a study was conducted to investigate the differences in the length of stay of a trip for pre- and post-retirees. A sample of 692 travelers were asked how long they stayed on a typical trip. The observed results of the study are found below.
Number of Nights | Pre-retirement | Post-retirement | Total |
4−7 | 240 | 160 | 400 |
8−13 | 83 | 67 | 150 |
14−21 | 32 | 57 | 89 |
22 or more | 13 | 40 | 53 |
Total | 368 | 324 | 692 |
With this information, construct a table of expected numbers.
Number of Nights | Pre-retirement | Post-retirement |
4-7 | ||
8−13 | ||
14-21 | ||
22 or more |
The chi-squared value is ?2= 35.8310290188111
Using α=0.05, consider a test of ?0: length of stay and retirement are not related vs. ??: length of stay and retirement are related. Note that this problem involves a 4×2 contingency table and that the magic number for evaluating such a table at theα=0.05 level of significance is magic number = 7.81.
The final conclusion is
A. Accept ?0. There is not sufficient evidence to
conclude that the length of stay is related to retirement.
B. Reject ?0.There is sufficient evidence to
conclude that the length of stay is related to retirement.
Expected Value Calculation:
Thus, final conlusion is:
B. Reject ?0.There is sufficient evidence to conclude that the length of stay is related to retirement.