QUESTION 1

The Central Limit Theorem tells us that:

		the shape of all sampling distributions of sample means are normally distributed.
		the mean of the distribution of sample means is less than the mean of the parent population.
		the standard deviation of the distribution of sample means is the same as the standard deviation of the population.
		all of the above are true.
		none of the above are true.

1 points

QUESTION 2

The Central Limit Theorem

		says that s(x) approaches sigma(x) as sample size increases.
		says that any sampling distribution of a sample mean will be approximately normal regardless of the shape of the population distribution.
		says that both a and b will occur.
		says that x-bar approaches mu as sample size increases.

1 points

QUESTION 3

The Central Limit Theorem is of most value when we sample from a normal distribution.

		True
		False

1 points

QUESTION 4

As the sample size increases, the distribution of the sample mean approaches a normal distribution.

		True
		False

1 points

QUESTION 5

The Central Limit Theorem applies to the case of sampling from a normal distribution as well as other cases.

		True
		False

1 points

QUESTION 6

According to the Central Limit Theorem, the shape of the sampling distribution of x-bar (given that n = 30) will be normal, whether or not the shape of the population is normal.

		True
		False