Question

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.

Answer 1

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.

Answer 2

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

 

The central limit theorem states that if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement text annotation indicator, then the distribution of the sample means will be approximately normally distributed.

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

Therefore, the correct option is (b).

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