Question

QUESTION 11

The starting salaries of individuals with an MBA degree are normally distributed with a mean of $90,000 and a standard deviation of $20,000. What percentage of MBA's will have starting salaries of $77,000 to $99,000?

1. 27.99%
2. 42.07%
3. 30.50%
4. 41.58%

QUESTION 12

The starting salaries of individuals with an MBA degree are normally distributed with a mean of $90,000 and a standard deviation of $20,000. Suppose we randomly select 9 of these individuals with an MBA degree. What is the expected value of the average starting salary for these individuals?

	a.	$70,000
	b.	$80,000
	c.	$20,000
	d.	$90,000

QUESTION 13

The starting salaries of individuals with an MBA degree are normally distributed with a mean of $90,000 and a standard deviation of $20,000. Suppose we randomly select 16 of these individuals with an MBA degree. What is the standard deviation of the average starting salary for these individuals?

	a.	$4,000
	b.	$5,000
	c.	$20,000
	d.	$1,666.67

QUESTION 14

The starting salaries of individuals with an MBA degree are normally distributed with a mean of $90,000 and a standard deviation of $20,000. Suppose we randomly select 16 of these individuals with an MBA degree. What is the shape of the sampling distribution of the average starting salary for these individuals?

	a.	Normal
	b.	Normal because of the Central Limit Theorem
	c.	Normal because the distribution of the starting salaries of individuals with an MBA degree is normal
	d.	None of the above

QUESTION 15

The starting salaries of individuals with an MBA degree are normally distributed with a mean of $90,000 and a standard deviation of $20,000. Suppose we randomly select 16 of these individuals with an MBA degree. What is the probability that the average starting salary for these individuals is at least $85,800?

1. 0.7995
2. 0.9131
3. 0.2005
4. -0.2611

QUESTION 16

The sampling distribution of a sample mean is

	a.	the probability distribution of the sample mean.
	b.	insignificant, because the sample mean varies from sample to sample.
	c.	insignificant, because most of the time the sample mean is not equal to the true population mean.
	d.	always similar to the original population distribution.

QUESTION 17

A sample of 92 observations is taken from an infinite population. The sampling distribution of Xbar is approximately

	a.	normal because Xbar is always approximately normally distributed.
	b.	normal because the sample size is small in comparison to the population size.
	c.	normal because of the central limit theorem.
	d.	none of the above.

QUESTION 18

The sampling error is the

	a.	same as the standard error of the mean.
	b.	the absolute value of the difference between the sample mean and the population mean.
	c.	error caused by selecting a bad sample.
	d.	standard deviation multiplied by the sample size.

QUESTION 19

An estimate of a population parameter that provides an interval of values believed to contain the value of the parameter is known as the

	a.	confidence level
	b.	interval estimate
	c.	parameter value
	d.	point estimate

QUESTION 20

Since the sample size is always smaller than the population size, the sample mean

	a.	can be smaller, larger, or equal to the population mean.
	b.	must always be smaller than the population mean.
	c.	must be equal to the population mean.
	d.	must be larger than the population mean.

Answer 1

Question 11

P ( 77000 < X < 99000 )
Standardizing the value

Z = ( 77000 - 90000 ) / 20000
Z = -0.65
Z = ( 99000 - 90000 ) / 20000
Z = 0.45
P ( -0.65 < Z < 0.45 )
P ( 77000 < X < 99000 ) = P ( Z < 0.45 ) - P ( Z < -0.65 )
P ( 77000 < X < 99000 ) = 0.6736 - 0.2578
P ( 77000 < X < 99000 ) = 0.4158

Percentage = 0.4158 * 100 = 41.58%

Question 12

Question 13