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Multiple choice: Select the best answer for Exercises 65 to 68. The number of hours a
Chapter 7, Problem 68(choose chapter or problem)
Multiple choice: Select the best answer for Exercises 65 to 68. The number of hours a lightbulb burns before failing varies from bulb to bulb. The population distribution of burnout times is strongly skewed to the right. The central limit theorem says that (a) as we look at more and more bulbs, their average burnout time gets ever closer to the mean m for all bulbs of this type. (b) the average burnout time of a large number of bulbs has a sampling distribution with the same shape (strongly skewed) as the population distribution. (c) the average burnout time of a large number of bulbs has a sampling distribution with similar shape but not as extreme (skewed, but not as strongly) as the population distribution. (d) the average burnout time of a large number of bulbs has a sampling distribution that is close to Normal. (e) the average burnout time of a large number of bulbs has a sampling distribution that is exactly Normal.
Questions & Answers
QUESTION:
Multiple choice: Select the best answer for Exercises 65 to 68. The number of hours a lightbulb burns before failing varies from bulb to bulb. The population distribution of burnout times is strongly skewed to the right. The central limit theorem says that (a) as we look at more and more bulbs, their average burnout time gets ever closer to the mean m for all bulbs of this type. (b) the average burnout time of a large number of bulbs has a sampling distribution with the same shape (strongly skewed) as the population distribution. (c) the average burnout time of a large number of bulbs has a sampling distribution with similar shape but not as extreme (skewed, but not as strongly) as the population distribution. (d) the average burnout time of a large number of bulbs has a sampling distribution that is close to Normal. (e) the average burnout time of a large number of bulbs has a sampling distribution that is exactly Normal.
ANSWER:Step 1 of 2
Central limit theorem states that when n is large, the sampling distribution of the sampling mean is close to normal.
It is given that the population distribution of burnout times is strongly skewed to the right.