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Westkost [7]
3 years ago
7

The number of hours a lightbulb burns before failing varies from bulb to bulb. The population distribution of burnout times is s

trongly 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.
Mathematics
1 answer:
liubo4ka [24]3 years ago
6 0

ANSWER:

The average burnout time of a large number of bulbs has a sampling distribution that is close to Normal.

STEP-BY-STEP EXPLANATION:

The cental limit theorem states, that id the sample size is large (30 or more), then the sampling distribution of the sample means is approximately normal with mean ц and standar deviation б/\sqrt{n}

Thus the correct answer is the average burnout time of a large number of bulbs has a sampling distribution that is close to Normal.

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