Practice Test 8

Front 1

In practice, researchers collect a sample of size "n" and compute point estimates of population parameters.
Based on the Central Limit Theorem, how can sampling error be reduced?

Back 1

Increasing the sample size;

Front 2

What are the two population parameters that specify the location and dispersion for a normal distribution?

Back 2

µ or the population mean and σ^2 or the population variance

Front 3

What are the two population parameters that specify the location and dispersion for the sampling distribution of the mean?

Back 3

µ or the population mean and σ^2/ √n or the population standard error

Front 4

How is the Central Limit Theorem helpful when computing probabilities?

Back 4

The Central Limit Theorem allows the use of the normal distribution and the standard normal z to compute
probabilities.

Front 5

Sampling from a population may be preferred because studying all the items in a population may be too
_____________.

Back 5

costly

Front 6

Sampling from a population may be preferred because, contacting or listing the entire population would be
too ___________ consuming.

Back 6

time

Front 7

Sampling from a population may be preferred because, sometimes collecting statistics requires that products
be ___________.

Back 7

destroyed

Front 8

How many different samples of size 3 can be collected from a population of ten items? ___________

Back 8

120

Front 9

What type of sampling is it when a population is first divided into subgroups and then a sample is selected
from each subgroup? _________

Back 9

stratified random sampling

Front 10

Auditors may select every 20th file starting with say, the 5th file in the top drawer. Then file numbers 25, 45,
65, 85, . . . are audited. What type of sampling is this? _________________

Back 10

systematic

Front 11

What will the sampling distribution of the mean be if a population is normally distributed?

Back 11

normally distributed

Front 12

What is the name of the standard deviation of the sampling distribution of the sample means called?

Back 12

standard error of the mean

Front 13

The process of making statements about a population based on a sample from the population is called
______________________

Back 13

statistical inference

Front 14

What is a characteristic of a population called? _______________

Back 14

parameter

Front 15

What is the relationship of the standard deviation of the sampling distribution of the mean to the standard
deviation of the population under study? ___________

Back 15

smaller

Front 16

For a sampling distribution of the means, what percent of the means would be between ± 1.96 standard
deviations? ________________________

Back 16

95%

Front 17

As the sample size (n) increases, what happens to the spread or dispersion of the distribution of the sample
means? ___________

Back 17

decreases

Front 18

If the sample size equals the population size, what is the sampling error? _________

Back 18

zero

Front 19

For populations scattered in a wide area, what is the preferred technique for sampling? ____________

Back 19

cluster sampling

Front 20

Which sampling method would be best to use if the population can be divided into homogeneous
subgroups? ______________________

Back 20

stratified random sampling

Front 21

Which sampling method would you use if every k-th item in the population sequence is selected?
______________________

Back 21

systematic random sampling

Front 22

What is it called when all the items in a population have a chance of being selected in a sample?
A. Random sampling
B. z-score
C. Sampling error
D. Nonprobability sampling

Back 22

A. Random sampling

Front 23

What is the difference between a sample mean and the population mean called?
A. Standard error of the mean
B. Sampling error
C. Interval estimate
D. Point estimate

Back 23

B. Sampling error

Front 24

What sample statistic is used to estimate a population parameter?
A. Parameter
B. Sampling error
C. Point estimate
D. Interval estimate

Back 24

C.Interval estimate

Front 25

Suppose we select every fifth invoice in a file. What type of sampling is this?
A. Random
B. Cluster
C. Stratified
D. Systematic

Back 25

D. Systematic

Front 26

All possible samples of size n are selected from a population and the mean of each sample is determined.
What is the mean of the sample means?
A. Exactly the same as the population mean
B. Larger than the population mean
C. Smaller than the population mean
D. Cannot be estimated in advance

Back 26

A. Exactly the same as the population mean

Front 27

When dividing a population into subgroups so that a random sample from each subgroup can be collected, what type of sampling is used?
A. simple random sampling
B. systematic sampling
C. stratified random sampling
D. cluster sampling

Back 27

C. stratified random sampling

Front 28

The true sampling error is usually not known because
A. a sample is collected from a population
B. μ is a random variable
C. s2 is unknown
D. The sample mean cannot be computed

Back 28

A. a sample is collected from a population

Front 29

Based on the central limit theorem, the size of the sampling error is
A. Directly related to the sample size, i.e., the larger the sample size the larger the sampling error.
B. Directly related to the population mean, i.e., the larger the mean, the larger the sampling error
C. Inversely related to the sample size, i.e., the larger the sample size the smaller the sampling error.
D. Inversely related to the population standard deviation, i.e., the smaller the standard deviation, the larger the sampling error.

Back 29

C. Inversely related to the sample size, i.e., the larger the sample size the smaller the sampling error.

Front 30

As the size of the sample increases, what happens to the shape of the sampling means?
A. Cannot be predicted in advance
B. Approaches a normal distribution
C. Positively skewed
D. Negatively skewed

Back 30

B. Approaches a normal distribution

Front 31

A statewide sample survey is to be made. First, the state is subdivided into counties. Seven counties are
selected at random and further sampling is concentrated on these seven counties. What type of sampling is this?
A. Simple random
B. Nonproportional
D. Stratified random
D. Stratified random

Back 31

D. Stratified random

Front 32

Which of the following is the standard error of the mean?
A. σ 
B. x/n
C. σ/ √ n
D. s

Back 32

C. σ/ √ n

Front 33

Mileage tests were conducted on a randomly selected sample of 100 newly developed automobile tires. The average tread wear was found to be 50,000 miles with a standard deviation of 3,500 miles. What is the best estimate of the average tread life in miles for the entire population of these tires?
A. 50,000
B. 3,500
C. (50,000/100)
D. (3,500/100)

Back 33

A. 50,000

Front 34

The mean of all possible sample means is equal to the
A. population variance.
B. σ^2/ n
C. sample variance.
D. population mean.

Back 34

D. population mean.

Front 35

Sampling error is the difference between a corresponding sample statistic and the
A. sample mean.
B. biased sample.
C. population parameter.
D. chance error.

Back 35

C. population parameter.

Front 36

For a population that is not normally distributed, the distribution of the sample means will
A. be negatively skewed.
B. approach the normal distribution.
C. be positively skewed.
D. take the same shape as the population.

Back 36

B. approach the normal distribution.

Front 37

True or False:
In stratified random sampling, a population is divided into strata using naturally occurring geographic or other boundaries. Then strata are randomly selected and a random sample is collected from each strata.

Back 37

False

Front 38

True or False:
In cluster sampling, a population is divided into clusters using naturally occurring geographic or other
boundaries. Then clusters are randomly selected and a random sample is collected from each cluster.

Back 38

True

Front 39

True or False:
Sampling a population is often necessary because the cost of studying all the items in the population is
prohibitive.

Back 39

True

Front 40

True or False:
It is often not feasible to study the entire population because it is impossible to observe all the items in the
population.

Back 40

True

Front 41

True or False:
A simple random sample assumes that each item or person in the population has an equal chance of being
included.

Back 41

True

Front 42

True or False:
The standard error of the mean is also be called sampling error.

Back 42

False

Front 43

True or False:
When systematic random sampling is used, the central limit theorem cannot be applied.

Back 43

False

Front 44

True or False:
When using stratified random sampling, the sampling error will be zero.

Back 44

False

Front 45

True or False:
In cluster sampling, a population is divided into subgroups called clusters and a sample is randomly
selected from each cluster.

Back 45

False

Front 46

True or False:
In stratified random sampling, a population is divided into subgroups called strata and a sample is randomly
selected from each stratum.

Back 46

True

Front 47

True or False:
When systematic random sampling is used, the central limit theorem cannot be applied.

Back 47

False

Front 48

True or False:
When using systematic random sampling, the sampling error will be zero.

Back 48

False

Front 49

True or False:
If probability sampling is done, each item in the population has a chance of being chosen.

Back 49

True

Front 50

True or False:
The items or individuals of the population are arranged in a file drawer alphabetically by date received. A random starting point is selected and then every kth member of the population is selected for the sample. This sampling method is called simple random sampling.

Back 50

False

Front 51

True or False:
If the size of a sample equals the size of the population, we would not expect any error in estimating the population parameter.

Back 51

True

Front 52

True or False:
We can expect some difference between sample statistics and the corresponding population parameters. This difference is called the sampling error.

Back 52

True

Front 53

True or False:
A sampling distribution of the means is a probability distribution consisting of a list of all possible sample
means of a given sample size selected from a population and the probability of occurrence associated with each sample mean.

Back 53

True

Front 54

True or False:
The central limit theorem implies that sampling with an adequate sample size provides good estimates of
population parameters.

Back 54

True

Front 55

True or False:
The central limit theorem implies that samples of size one or two are adequate to estimate population
parameters.

Back 55

False

Front 56

True or False:
If a population is not normally distributed, the sampling distribution of the sample means tends to
approximate a normal distribution.

Back 56

True

Front 57

True or False:
The Central Limit Theorem states that for a sufficiently large sample the sampling distribution of the means of all possible samples of size n generated from the population will be approximately normally distributed with the mean of the sampling distribution equal to σ^2 and the variance equal to σ^(2/n) .

Back 57

False

Front 58

True or False:
The Central Limit Theorem states that if the sample size, n, is sufficiently large, the sampling distribution of the means will be approximately normal no matter whether the population is normally distributed, skewed, or uniform.

Back 58

True

Front 59

True or False:
Fish and game wardens estimate the average weight of the fish or game population by using creel checks
and other devices. Based on this sample data, a warden might estimate that the mean weight of Coho salmon caught in Lake Michigan is 2.5 pounds. This single number is called a point estimate of the unknown population parameter.

Back 59

True

Front 60

True or False:
Based on the sampling distribution of the means and the central limit theorem, the sample mean can be used as a good estimator of the population mean, assuming that the size of the sample is sufficiently large.

Back 60

True

Front 61

True or False:
If 40 samples of size 21 were selected from a population of 22,493, we would expect the mean of the sample means and the population mean to be close but not exactly equal.

Back 61

True

Front 62

True or False:
An estimate of the population mean based on a large sample is less reliable than an estimate made using a
small sample.

Back 62

False

Front 63

True or False:
If the sample size keeps getting larger and larger and finally equals the size of the population, there would be no error in predicting the population mean because the sample size and the size of the population would be the same.

Back 63

True

Front 64

True or False:
The standard error of the mean will vary according to the size of the sample. As the sample size n gets
larger, the variability of the sample means gets smaller.

Back 64

True

Front 65

True or False:
To determine the value of the standard error of the mean, the total error is divided by the sample size.

Back 65

False