Question 1

The sampling method in which a population is divided into blocks and then selected by choosing a random mechanism is called a

Accepted Answer

A)   random sampling
B)   systematic sampling
C)   stratified sampling
D)   cluster sampling B

Question 2

The standard error of an estimate is the standard deviation of the sampling distribution of the estimate.It measures how much estimates from different samples vary.

Accepted Answer

A) True 
 B)False  True

Question 3

The reason the Central Limit Theorem (CLT)is such an important result in statistics is because:

Accepted Answer

A)   The CLT allows us to assume that the population distribution is approximately normal,provided n is reasonably large
B)   The CLT allows us to estimate the population mean without knowing the exact form of the population distribution,provided n is reasonably large
C)   The CLT allows us to construct confidence intervals for the population mean without knowing the exact form of the population distribution,provided n is reasonably large
D)   All of these options D

Question 4

An estimator is said to be unbiased if the mean of its sampling distribution equals the value of the population parameter being estimated.

Accepted Answer

A) True 
 B)False

Question 5

The sampling mean $\bar { X }$
Is the estimate for the population mean $\mu$
)

Accepted Answer

A)   random
B)   point
C)   simple
D)   interval

Question 6

Which of the following statements are correct?

Accepted Answer

A)   A point estimate is an estimate of the range of a population parameter
B)   A point estimate is a single value estimate of the value of a population parameter
C)   A point estimate is an unbiased estimator if its standard deviation is the same as the actual value of the population standard deviation
D)   All of these options

Question 7

An unbiased estimate is a point estimate such that the mean of its sampling distribution is equal to the true value of the population parameter being estimated.

Accepted Answer

A) True 
 B)False

Question 8

The theorem that states that the sampling distribution of the sample mean $\bar { X }$
Is approximately normal when the sample size n is reasonably large is known as the:

Accepted Answer

A)   central limit theorem
B)   central tendency theorem
C)   simple random sample theorem
D)   point estimate theorem

Question 9

The standard deviation of $\bar { X }$
Is usually called the

Accepted Answer

A)   standard error of the mean
B)   standard error of the sample
C)   standard error of the population
D)   randomized standard error

Question 10

Simple random sampling can result in under-representation or over-representation of certain segments of the population.This is one of several reasons that simple random samples are almost never used in real applications.

Accepted Answer

A) True 
 B)False

Question 11

The key to using stratified sampling is:

Accepted Answer

A)   identifying the strata
B)   selecting the appropriate strata
C)   defining the strata
D)   randomizing the strata

Question 12

Which of the following are reasons for why simple random sampling is used infrequently in real applications?

Accepted Answer

A)   Samples can be spread over a large geographic region
B)   Simple random sampling requires that all sampling units be identified prior to sampling
C)   Simple random sampling can result in underrepresentation or overrepresentation of certain segments of the population
D)   All of these options

Question 13

The approximate standard error of the sample mean is calculated as:

Accepted Answer

A)   σIn\sigma I \sqrt { n }σInc-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429c69,-144,104.5,-217.7,106.5,-221l0 -0c5.3,-9.3,12,-14,20,-14H400000v40H845.2724s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47zM834 80h400000v40h-400000z"/>​ 
B)   sIns I \sqrt { n }sInc-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429c69,-144,104.5,-217.7,106.5,-221l0 -0c5.3,-9.3,12,-14,20,-14H400000v40H845.2724s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47zM834 80h400000v40h-400000z"/>​ 
C)   2σ/n2 \sigma/ \sqrt { n }2σ/nc-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429c69,-144,104.5,-217.7,106.5,-221l0 -0c5.3,-9.3,12,-14,20,-14H400000v40H845.2724s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47zM834 80h400000v40h-400000z"/>​ 
D)   2s/n2 s / \sqrt { n }2s/nc-2.7,0,-7.17,-2.7,-13.5,-8c-5.8,-5.3,-9.5,-10,-9.5,-14c0,-2,0.3,-3.3,1,-4c1.3,-2.7,23.83,-20.7,67.5,-54c44.2,-33.3,65.8,-50.3,66.5,-51c1.3,-1.3,3,-2,5,-2c4.7,0,8.7,3.3,12,10s173,378,173,378c0.7,0,35.3,-71,104,-213c68.7,-142,137.5,-285,206.5,-429c69,-144,104.5,-217.7,106.5,-221l0 -0c5.3,-9.3,12,-14,20,-14H400000v40H845.2724s-225.272,467,-225.272,467s-235,486,-235,486c-2.7,4.7,-9,7,-19,7c-6,0,-10,-1,-12,-3s-194,-422,-194,-422s-65,47,-65,47zM834 80h400000v40h-400000z"/>​

Question 14

A point estimate is a single numeric value,a "best guess" of a population parameter,calculated from the sample data.

Accepted Answer

A) True 
 B)False

Question 15

The opportunity for nonsampling error is increased by:

Accepted Answer

A)   larger sample sizes
B)   smaller sample sizes
C)   affluent samples
D)   educated samples

Question 16

A sample in which the sampling units are chosen from the population by means of a random mechanism is a

Accepted Answer

A)   probability sample
B)   judgmental sample
C)   stratified sample
D)   systematic sample

Question 17

When a portion of the sample does not respond to the survey,results.

Accepted Answer

A)   measurement error
B)   nonresponse bias
C)   sampling error
D)   systematic failure
E)   nonlinear error

Question 18

The randomized response technique is a way of getting at sensitive information to avoid estimation errors due to nontruthful responses.

Accepted Answer

A) True 
 B)False

Question 19

It is customary to approximate the standard error of the sample mean $\sigma / \sqrt { n }$ 
by substituting the sample standard deviation s for $\sigma$ 
in the formula: SE( $\bar { X }$ 
)= $\sigma / \sqrt { n }$ 
.

Accepted Answer

A) True 
 B)False

Question 20

The size of a sample can be selected by first determining the desired standard error and then using the formula $S E ( X ) = \sigma I \sqrt { n }$ 
to calculate n.

Accepted Answer

A) True 
 B)False

Exam 7: Sampling and Sampling Distributions

The sampling method in which a population is divided into blocks and then selected by choosing a random mechanism is called a

The standard error of an estimate is the standard deviation of the sampling distribution of the estimate.It measures how much estimates from different samples vary.

The reason the Central Limit Theorem (CLT) is such an important result in statistics is because:

An estimator is said to be unbiased if the mean of its sampling distribution equals the value of the population parameter being estimated.

The sampling mean $\bar { X }$ Is the estimate for the population mean $\mu$ )

Which of the following statements are correct?

An unbiased estimate is a point estimate such that the mean of its sampling distribution is equal to the true value of the population parameter being estimated.

The theorem that states that the sampling distribution of the sample mean $\bar { X }$ Is approximately normal when the sample size n is reasonably large is known as the:

The standard deviation of $\bar { X }$ Is usually called the

Simple random sampling can result in under-representation or over-representation of certain segments of the population.This is one of several reasons that simple random samples are almost never used in real applications.

The key to using stratified sampling is:

Which of the following are reasons for why simple random sampling is used infrequently in real applications?

The approximate standard error of the sample mean is calculated as:

A point estimate is a single numeric value,a "best guess" of a population parameter,calculated from the sample data.

The opportunity for nonsampling error is increased by:

A sample in which the sampling units are chosen from the population by means of a random mechanism is a

When a portion of the sample does not respond to the survey,results.

The randomized response technique is a way of getting at sensitive information to avoid estimation errors due to nontruthful responses.

It is customary to approximate the standard error of the sample mean $\sigma / \sqrt { n }$ by substituting the sample standard deviation s for $\sigma$ in the formula: SE( $\bar { X }$ )= $\sigma / \sqrt { n }$ .

The size of a sample can be selected by first determining the desired standard error and then using the formula $S E ( X ) = \sigma I \sqrt { n }$ to calculate n.

Exam 7: Sampling and Sampling Distributions

The sampling method in which a population is divided into blocks and then selected by choosing a random mechanism is called a

The standard error of an estimate is the standard deviation of the sampling distribution of the estimate.It measures how much estimates from different samples vary.

The reason the Central Limit Theorem (CLT) is such an important result in statistics is because:

An estimator is said to be unbiased if the mean of its sampling distribution equals the value of the population parameter being estimated.

The sampling mean Xˉ\bar { X }Xˉ Is the estimate for the population mean μ\muμ )

Which of the following statements are correct?

An unbiased estimate is a point estimate such that the mean of its sampling distribution is equal to the true value of the population parameter being estimated.

The theorem that states that the sampling distribution of the sample mean Xˉ\bar { X }Xˉ Is approximately normal when the sample size n is reasonably large is known as the:

The standard deviation of Xˉ\bar { X }Xˉ Is usually called the

Simple random sampling can result in under-representation or over-representation of certain segments of the population.This is one of several reasons that simple random samples are almost never used in real applications.

The key to using stratified sampling is:

Which of the following are reasons for why simple random sampling is used infrequently in real applications?

The approximate standard error of the sample mean is calculated as:

A point estimate is a single numeric value,a "best guess" of a population parameter,calculated from the sample data.

The opportunity for nonsampling error is increased by:

A sample in which the sampling units are chosen from the population by means of a random mechanism is a

When a portion of the sample does not respond to the survey,results.

The randomized response technique is a way of getting at sensitive information to avoid estimation errors due to nontruthful responses.

It is customary to approximate the standard error of the sample mean σ/n\sigma / \sqrt { n }σ/n​ by substituting the sample standard deviation s for σ\sigmaσ in the formula: SE( Xˉ\bar { X }Xˉ )= σ/n\sigma / \sqrt { n }σ/n​ .

The size of a sample can be selected by first determining the desired standard error and then using the formula SE(X)=σInS E ( X ) = \sigma I \sqrt { n }SE(X)=σIn​ to calculate n.

The sampling mean $\bar { X }$ Is the estimate for the population mean $\mu$ )

The theorem that states that the sampling distribution of the sample mean $\bar { X }$ Is approximately normal when the sample size n is reasonably large is known as the:

The standard deviation of $\bar { X }$ Is usually called the

It is customary to approximate the standard error of the sample mean $\sigma / \sqrt { n }$ by substituting the sample standard deviation s for $\sigma$ in the formula: SE( $\bar { X }$ )= $\sigma / \sqrt { n }$ .

The size of a sample can be selected by first determining the desired standard error and then using the formula $S E ( X ) = \sigma I \sqrt { n }$ to calculate n.