Is the variance for the amount of money, in dollars, that shoppers spend on Saturdays at the mall the same as the variance for the amount of money that shoppers spend on Sundays at the mall? Suppose that the tables below show the results of a study:
Saturday:
48 | 69.6 | 76 | 80.3 | 85.9 |
60 | 101.5 | 109.6 | 87.6 | 89 |
59.1 | 92.4 | 56.5 | 53.7 |
(Note: The average and the standard deviation of the data are respectively 76.4 dollars and 19.04 dollars.)
Sunday:
96.3 | 60.4 | 81.9 | 85.6 | 90.9 |
99 | 67.5 | 89.4 | 66.6 | 86.6 |
54.3 | 77.9 | 83.3 | 109.7 | 61.9 |
89.8 | 84.3 | 77.4 | 69.4 | 76 |
(Note: The average and the standard deviation of the data are respectively 80.4 dollars and 14.08 dollars.)
Use a 10% significance level to test the claim that the standard deviation for the amount of money that shoppers spend on Saturday is greater than the standard deviation for the amount of money that shoppers spend on Sunday.
Procedure:
Assumptions: (select everything that applies)
Step 1. Hypotheses Set-Up:
= | , where the and the units are |
, and the test is |
Step 2. The significance level %
Step 3. Compute the value of the test statistic: = (Round the answer to 3 decimal places)
Step 4. Testing Procedure: (Round the answers to 3 decimal places)
CVA | PVA |
Provide the critical value(s) for the Rejection Region: | Compute the P-value of the test statistic: |
left CV is and right CV is | P-value is |
Step 5. Decision:
CVA | PVA |
Is the test statistic in the rejection region? | Is the P-value less than the significance level? |
Conclusion:
Step 6. Interpretation:
At 10% significance level we have sufficient evidence to reject the null hypothesis in favor of the alternative hypothesis.
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