ch 15* the number of hours a battery lasts before failing varies from battery to battery. the distribution…

ch 15* the number of hours a battery lasts before failing varies from battery to battery. the distribution of failure times follows a distribution which is strongly skewed to the right. the central limit theorem says that\n\no the average failure time of a large number of batteries has a distribution of the same shape (strongly skewed) as the distribution for individual batteries.\n\nthe average failure time of a large number of batteries has a distribution that is close to normal.\n\no as we look at more and more batteries, their average failure time gets ever closer to the mean μ for all batteries of this type.

ch 15* the number of hours a battery lasts before failing varies from battery to battery. the distribution of failure times follows a distribution which is strongly skewed to the right. the central limit theorem says that\n\no the average failure time of a large number of batteries has a distribution of the same shape (strongly skewed) as the distribution for individual batteries.\n\nthe average failure time of a large number of batteries has a distribution that is close to normal.\n\no as we look at more and more batteries, their average failure time gets ever closer to the mean μ for all batteries of this type.

Answer

Brief Explanations:

The central limit theorem states that for a large - sample size, the sampling distribution of the sample mean will be approximately normal regardless of the shape of the population distribution. Here, for a large number of batteries, the average failure time (sample mean) will have a distribution close to normal despite the right - skewed distribution of individual battery failure times.

Answer:

the average failure time of a large number of batteries has a distribution that is close to Normal