Question 1

Which of the following is an example of non-sampling errors?

Accepted Answer

A)  Errors that arise from the recording of incorrect responses. 
B)  Errors that arise when responses are not obtained from some members of the sample. 
C)  Errors that arise when some members of the target population cannot possibly be selected in the sample. 
D)  All of these choices are correct. 
A)  Errors that arise from the recording of incorrect responses. 
B)  Errors that arise when responses are not obtained from some members of the sample. 
C)  Errors that arise when some members of the target population cannot possibly be selected in the sample. 
D)  All of these choices are correct. D

Question 2

A politician wants to estimate the mean age of voters in her electorate. Unfortunately, she does not have a complete list of voters. Describe a sampling plan that would be suitable for her purposes.

Accepted Answer

Use cluster sampling, letting each subdivision in the electorate represent a cluster.

Question 3

When the population is divided into mutually exclusive sets, and then a simple random sample is drawn from each set, this is called:

Accepted Answer

A)  simple random sampling. 
B)  stratified random sampling. 
C)  cluster sampling. 
D)  selection bias. 
A)  simple random sampling. 
B)  stratified random sampling. 
C)  cluster sampling. 
D)  selection bias. B

Question 4

When every possible sample of size n has the same chance of being selected, this is called:

Accepted Answer

A)  simple random sampling. 
B)  stratified random sampling. 
C)  cluster sampling. 
D)  sampling error. 
A)  simple random sampling. 
B)  stratified random sampling. 
C)  cluster sampling. 
D)  sampling error.

Question 5

Sampling error may be reduced by increasing the sample size but non-sampling error cannot be reduced by increasing the sample size.

Accepted Answer

A) True 
 B)False

Question 6

Stratified sampling is preferred over cluster sampling when it is difficult or costly to develop a complete list of the population members.

Accepted Answer

A) True 
 B)False

Question 7

Which of the following is a characteristic of cluster sampling?

Accepted Answer

A)  The population is not divided. 
B)  The population is divided into groups of similar characteristics. 
C)  The population is divided into homogeneous groups. 
D)  The population is divided into heterogeneous groups 
A)  The population is not divided. 
B)  The population is divided into groups of similar characteristics. 
C)  The population is divided into homogeneous groups. 
D)  The population is divided into heterogeneous groups

Question 8

Which of the following is not an example of primary data?

Accepted Answer

A)  Data published by the United States Bureau of Census. 
B)  Data published by the Australian Bureau of Statistics. 
C)  Data published by the Australian Stock Exchange (ASX). 
D)  Data published by the United Nations Statistical Division. 
A)  Data published by the United States Bureau of Census. 
B)  Data published by the Australian Bureau of Statistics. 
C)  Data published by the Australian Stock Exchange (ASX). 
D)  Data published by the United Nations Statistical Division.

Question 9

Briefly describe three types of non-sampling errors.

Accepted Answer

• Errors in data acquisition are errors

Question 10

The target population is the population about which we want to draw inferences, whereas the sampled population is the actual population from which the sample has been drawn.

Accepted Answer

A) True 
 B)False

Question 11

A variable is any characteristic of a population or sample.

Accepted Answer

A) True 
 B)False

Question 12

A customer advocacy group would like to compare customers' satisfaction with four financial institutions. Describe a sampling plan that would be suitable for studying customers' satisfaction and for comparing the banks.

Accepted Answer

Stratified random samples shou

Question 13

Which of the following sampling plans uses random methods of selection?

Accepted Answer

A)  Simple random sampling. 
B)  Simple random sampling, stratified random sampling and cluster sampling. 
C)  Simple random sampling and stratified random sampling. 
D)  Cluster sampling. 
A)  Simple random sampling. 
B)  Simple random sampling, stratified random sampling and cluster sampling. 
C)  Simple random sampling and stratified random sampling. 
D)  Cluster sampling.

Question 14

Which of the following refers to the differences between the sample and the population that exist only because of the observations that happened to be selected for the sample?

Accepted Answer

A)  Response bias 
B)  Non-response bias 
C)  Sampling error 
D)  Non-sampling error 
A)  Response bias 
B)  Non-response bias 
C)  Sampling error 
D)  Non-sampling error

Question 15

Describe the key differences between numerical data and nominal data.

Accepted Answer

Numerical data is observations that are

Question 16

Which of the following must be avoided in designing a questionnaire?

Accepted Answer

A)  Dichotomous questions. 
B)  Leading questions. 
C)  Open-ended questions. 
D)  Demographic questions. 
A)  Dichotomous questions. 
B)  Leading questions. 
C)  Open-ended questions. 
D)  Demographic questions.

Question 17

A professor of economics intends to compare the performances of first year students at the four campuses of the university. In order to do so, she selects a random sample of 40 students from each campus. What is this type of sampling called?

Accepted Answer

A)  Stratified random sampling. 
B)  Simple random sampling. 
C)  Cluster sampling. 
D)  None of these choices are correct. 
A)  Stratified random sampling. 
B)  Simple random sampling. 
C)  Cluster sampling. 
D)  None of these choices are correct.

Exam 2: Types of Data, Data Collection and Sampling

Which of the following is an example of non-sampling errors?

A politician wants to estimate the mean age of voters in her electorate. Unfortunately, she does not have a complete list of voters. Describe a sampling plan that would be suitable for her purposes.

When the population is divided into mutually exclusive sets, and then a simple random sample is drawn from each set, this is called:

When every possible sample of size n has the same chance of being selected, this is called:

Sampling error may be reduced by increasing the sample size but non-sampling error cannot be reduced by increasing the sample size.

Stratified sampling is preferred over cluster sampling when it is difficult or costly to develop a complete list of the population members.

Which of the following is a characteristic of cluster sampling?

Which of the following is not an example of primary data?

Briefly describe three types of non-sampling errors.

The target population is the population about which we want to draw inferences, whereas the sampled population is the actual population from which the sample has been drawn.

A variable is any characteristic of a population or sample.

A customer advocacy group would like to compare customers' satisfaction with four financial institutions. Describe a sampling plan that would be suitable for studying customers' satisfaction and for comparing the banks.

Which of the following sampling plans uses random methods of selection?

Which of the following refers to the differences between the sample and the population that exist only because of the observations that happened to be selected for the sample?

Describe the key differences between numerical data and nominal data.

Which of the following must be avoided in designing a questionnaire?

A professor of economics intends to compare the performances of first year students at the four campuses of the university. In order to do so, she selects a random sample of 40 students from each campus. What is this type of sampling called?

What Is Statistics

Graphical Descriptive Methods Nominal Data

Graphical Descriptive Techniques Numerical Data

Numerical Descriptive Measures

Probability

Random Variables and Discrete Probability Distributions

Continuous Probability Distributions

Statistical Inference: Introduction

Sampling Distributions

Estimation: Describing a Single Population

Estimation: Comparing Two Populations

Hypothesis Testing: Describing a Single Population

Hypothesis Testing: Comparing Two Populations

Inference About Population Variances

Analysis of Variance

Additional Tests for Nominal Data: Chi-Squared Tests

Simple Linear Regression and Correlation

Multiple Regression

Model Building

Nonparametric Techniques

Statistical Inference: Conclusion

Time-Series Analysis and Forecasting

Index Numbers

Decision Analysis

Filters