aianjie

 

The correct answer is A

The central limit theorem tells us that for a population with a mean m and a finite variance σ2, the sampling distribution of the sample means of all possible samples of size n will approach a normal distribution with a mean equal to m and a variance equal to σ2 / n as n gets large.

aianjie

 

2、The central limit theorem states that, for any distribution, as n gets larger, the sampling distribution:

A) becomes larger.

B) becomes smaller.

C) approaches the mean.

D) approaches a normal distribution.

aianjie

 

8、If n is large and the population standard deviation is unknown, the standard error of the sampling distribution of the sample mean is equal to the:

A) population standard deviation divided by the sample size. 

B) sample standard deviation divided by the square root of the sample size.

C) population standard deviation multiplied by the sample size.

D) sample standard deviation divided by the sample size. 

aianjie

 

The correct answer is

The formula for the standard error when the population standard deviation is unknown is:

 

 

[attach]13851[/attach]

aianjie

 

The correct answer is A

 

 

[attach]13850[/attach]

aianjie

 

The correct answer is B

 

 

[attach]13849[/attach]

aianjie

 

7、The population mean for equity returns is 14 percent with a standard deviation of 2 percent. If a random sample of 49 returns is drawn, what is the standard error of the sample mean?

A) 0.29%.

B) 0.04%.

C) 2.00%.

D) 7.00%. 

aianjie

 

The correct answer is B

The standard error of the sample mean equals the standard deviation of the population divided by the square root of the sample size: 50 / 1001/2 = 5.

aianjie

 

5、A population has a mean of 20,000 and a standard deviation of 1,000. Samples of size n = 2,500 are taken from this population. What is the standard error of the sample mean?

A) 0.04.

B) 20.00.

C) 400.00.

D) 8.00.

aianjie

 

The correct answer is B

The standard error of the sample mean is estimated by dividing the standard deviation of the sample by the square root of the sample size: sx = s / n1/2 = 1000 / (2500)1/2 = 1000 / 50 = 20.