Question 1

There is an approximately _____% chance that any particular   will be within two standard deviations of the population mean (   ).

Accepted Answer

A) 90 
B) 95 
C) 99 
D) 99.7 
A) 90 
B) 95 
C) 99 
D) 99.7

Question 2

The probability of being chosen in a simple random sample of size n from a population of size N is

Accepted Answer

A) 1/N. 
B) N - 1/n. 
C) N/n. 
D) n/N. 
A) 1/N. 
B) N - 1/n. 
C) N/n. 
D) n/N.

Question 3

It is customary to approximate the standard error of the sample mean   by substituting the sample standard deviation s for   in the formula: SE(   )=   .

Accepted Answer

A) True 
 B)False

Question 4

Simple random samples are samples in which every possible sample of size n from the population has the same probability of being chosen.

Accepted Answer

A) True 
 B)False

Question 5

The sampling mean   is the ____ estimate for the population mean   .

Accepted Answer

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

Question 6

The defining property of a simple random sample is that

Accepted Answer

A) every possible sample of a particular size has the same chance of being chosen. 
B) it is the easiest method to access samples that are chosen. 
C) it requires the fewest samples necessary for statistical significance. 
D) every kth subject is chosen as a sample. 
A) every possible sample of a particular size has the same chance of being chosen. 
B) it is the easiest method to access samples that are chosen. 
C) it requires the fewest samples necessary for statistical significance. 
D) every kth subject is chosen as a sample.

Question 7

Selecting a random sample from each identifiable subgroup within a population is called _____ sampling.

Accepted Answer

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

Question 8

An estimator is said to be biased if the mean of its sampling distribution is not equal to the value of the population parameter being estimated.

Accepted Answer

A) True 
 B)False

Question 9

The sampling distribution of any point estimate (such as the sample mean or proportion)is the distribution of the point estimates we would obtain from all possible samples of a given size drawn from the population.

Accepted Answer

A) True 
 B)False

Question 10

Potential sample members,called sampling units,may be

Accepted Answer

A) people. 
B) companies. 
C) households. 
D) all of these choices. 
A) people. 
B) companies. 
C) households. 
D) all of these choices.

Question 11

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

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 choices are valid reasons. 
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 choices are valid reasons.

Question 13

The central limit theorem (CLT)states that the sampling distribution of the mean is approximately normal,no matter what the distribution of the population,as long as the sample size is large enough.

Accepted Answer

A) True 
 B)False

Question 14

The averaging effect means that as you average more and more observations from a given distribution,the variance of the average

Accepted Answer

A) increases. 
B) decreases. 
C) is unaffected. 
D) could either increase,decrease,or stay the same. 
A) increases. 
B) decreases. 
C) is unaffected. 
D) could either increase,decrease,or stay the same.

Question 15

If the sample size is greater than 30,the Central Limit Theorem (CLT)will always guarantee that the sampling distribution of the sample mean is approximately normal.

Accepted Answer

A) True 
 B)False

Question 16

Identifiable subpopulations within a population are called

Accepted Answer

A) clusters. 
B) samples. 
C) blocks. 
D) strata. 
A) clusters. 
B) samples. 
C) blocks. 
D) strata.

Question 17

The sampling distribution of the mean will have the same mean as the original population from which the samples were drawn.

Accepted Answer

A) True 
 B)False

Question 18

We can measure the accuracy of judgmental samples by applying some simple rules of probability.This way,judgmental samples are not likely to contain our built-in biases.

Accepted Answer

A) True 
 B)False

Question 19

A judgmental sample is a sample in which the

Accepted Answer

A) sampling units are chosen using a random number table. 
B) quality of sampling units judged before they are added to the sample. 
C) sampling units are chosen according to the sampler's judgment. 
D) sampling units condemn the sampling method used. 
A) sampling units are chosen using a random number table. 
B) quality of sampling units judged before they are added to the sample. 
C) sampling units are chosen according to the sampler's judgment. 
D) sampling units condemn the sampling method used.

Question 20

Systematic sampling is generally similar to simple random sampling in its statistical properties.

Accepted Answer

A) True 
 B)False

There is an approximately _____% chance that any particular will be within two standard deviations of the population mean ( ).

The probability of being chosen in a simple random sample of size n from a population of size N is

It is customary to approximate the standard error of the sample mean by substituting the sample standard deviation s for in the formula: SE( )= .

Simple random samples are samples in which every possible sample of size n from the population has the same probability of being chosen.

The sampling mean is the ____ estimate for the population mean .

The defining property of a simple random sample is that

Selecting a random sample from each identifiable subgroup within a population is called _____ sampling.

An estimator is said to be biased if the mean of its sampling distribution is not equal to the value of the population parameter being estimated.

The sampling distribution of any point estimate (such as the sample mean or proportion)is the distribution of the point estimates we would obtain from all possible samples of a given size drawn from the population.

Potential sample members,called sampling units,may be

The standard deviation of is usually called the

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

The central limit theorem (CLT)states that the sampling distribution of the mean is approximately normal,no matter what the distribution of the population,as long as the sample size is large enough.

The averaging effect means that as you average more and more observations from a given distribution,the variance of the average

If the sample size is greater than 30,the Central Limit Theorem (CLT)will always guarantee that the sampling distribution of the sample mean is approximately normal.

Identifiable subpopulations within a population are called

The sampling distribution of the mean will have the same mean as the original population from which the samples were drawn.

We can measure the accuracy of judgmental samples by applying some simple rules of probability.This way,judgmental samples are not likely to contain our built-in biases.

A judgmental sample is a sample in which the

Systematic sampling is generally similar to simple random sampling in its statistical properties.

Introduction to Business Analytics

Describing the Distribution of a Variable

Finding Relationships Among Variables

Business Intelligence Bifor Data Analysis

Probability and Probability Distributions

Decision Making Under Uncertainty

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

Exam 7: Sampling and Sampling Distributions

There is an approximately _____% chance that any particular will be within two standard deviations of the population mean ( ).

The probability of being chosen in a simple random sample of size n from a population of size N is

It is customary to approximate the standard error of the sample mean by substituting the sample standard deviation s for in the formula: SE( )= .

Simple random samples are samples in which every possible sample of size n from the population has the same probability of being chosen.

The sampling mean is the ____ estimate for the population mean .

The defining property of a simple random sample is that

Selecting a random sample from each identifiable subgroup within a population is called _____ sampling.

An estimator is said to be biased if the mean of its sampling distribution is not equal to the value of the population parameter being estimated.

The sampling distribution of any point estimate (such as the sample mean or proportion)is the distribution of the point estimates we would obtain from all possible samples of a given size drawn from the population.

Potential sample members,called sampling units,may be

The standard deviation of is usually called the

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

The central limit theorem (CLT)states that the sampling distribution of the mean is approximately normal,no matter what the distribution of the population,as long as the sample size is large enough.

The averaging effect means that as you average more and more observations from a given distribution,the variance of the average

If the sample size is greater than 30,the Central Limit Theorem (CLT)will always guarantee that the sampling distribution of the sample mean is approximately normal.

Identifiable subpopulations within a population are called

The sampling distribution of the mean will have the same mean as the original population from which the samples were drawn.

We can measure the accuracy of judgmental samples by applying some simple rules of probability.This way,judgmental samples are not likely to contain our built-in biases.

A judgmental sample is a sample in which the

Systematic sampling is generally similar to simple random sampling in its statistical properties.

Introduction to Business Analytics

Describing the Distribution of a Variable

Finding Relationships Among Variables

Business Intelligence Bifor Data Analysis

Probability and Probability Distributions

Decision Making Under Uncertainty

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Analysis of Variance and Experimental Design

Statistical Process Control

Filters