Final answer:
Andre's sample fails the large counts condition for a χ^2 goodness-of-fit test due to the expected count of people who neither approve nor disapprove of the Prime Minister's job, which is less than 5.
Step-by-step explanation:
Andre is interested in whether the percentages reported for national approval of the Prime Minister apply to his city. He collected a sample of 16 responses to perform a χ2 goodness-of-fit test, but before carrying out the test, he needs to check the large counts condition. This condition requires that all expected counts have to be at least 5 for the test to be valid. To determine if the sample fails this condition, we must calculate the expected counts:
- Expected count for 'Approve': 16 * 35% = 5.6
- Expected count for 'Disapprove': 16 * 35% = 5.6
- Expected count for 'Neither': 16 * 30% = 4.8
From the calculations above, it is clear that the observed counts for 'Approve' and 'Disapprove' meet the condition (since both are higher than 5), whereas the expected count for 'Neither' does not meet the condition, being less than the minimum required 5. Thus, the correct answer would be:
- E. The expected count of people who neither approve nor disapprove of the Prime Minister's job.