Test Bank
Testfor
Bank
Business
for Business
Statistics
Statistics
and Analytics
and Analytics
in Practice
in Practice
9th Edition
9th Edition
— Bowerman,
— Bowerman,
O’Connell
O’Connell
& Murphree,
& Murphree,
Full Chapters
Full Chapters
1–191–19
ISBN 9781260287844.docx
ISBN
2026-03-09
9781260287844
Chapter 01 Test Bank Static KEY
1. A population is a set of existing units.
TRUE
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 1 Easy
Learning Objective: 01-07 Describe the difference between a population and a sample.
Topic: Populations, Samples, and Traditional Statistics
2. If we examine some of the population measurements, we are conducting a census of the
population.
FALSE
A census is defined as examining all of the population measurements.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 2 Medium
Learning Objective: 01-07 Describe the difference between a population and a sample.
Topic: Populations, Samples, and Traditional Statistics
3. A random sample is selected so that every element in the population has the same chance of
being included in the sample.
TRUE
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 1 Easy
Learning Objective: 01-09 Explain the concept of random sampling and select a random sample. Topic: Random Sampling, Three Case Studies
That Illustrate Statistical Inference, and Statistical Modeling
4. An example of a quantitative variable is the manufacturer of a car.
FALSE
This is an example of a qualitative or categorical variable.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 1 Easy
Learning Objective: 01-02 Describe the difference between a quantitative variable and a qualitative variable.
Topic: Data
1-1
Copyright © 2017 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of
McGraw-Hill Education.
Bank forPage
Business
1 of 889
Statistics and Analytics in Practice 9th Edition — Bowerman,Page
O’Connell
1 & Murphree, Full Chapters 1–19 ISBN 9781260287844.docx
, Test Bank
Testfor
Bank
Business
for Business
Statistics
Statistics
and Analytics
and Analytics
in Practice
in Practice
9th Edition
9th Edition
— Bowerman,
— Bowerman,
O’Connell
O’Connell
& Murphree,
& Murphree,
Full Chapters
Full Chapters
1–191–19
ISBN 9781260287844.docx
ISBN
2026-03-09
9781260287844
5. An example of a qualitative variable is the mileage of a car.
FALSE
This is an example of a quantitative variable.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 1 Easy
Learning Objective: 01-02 Describe the difference between a quantitative variable and a qualitative variable.
Topic: Data
6. Statistical inference is the science of using a sample of measurements to make generalizations
about the important aspects of a population of measurements.
TRUE
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 2 Medium
Learning Objective: 01-08 Distinguish between descriptive statistics and statistical inference.
Topic: Populations, Samples, and Traditional Statistics
7. Time series data are data collected at the same time period.
FALSE
Time series data are collected over different time periods.
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 1 Easy
Learning Objective: 01-03 Describe the difference between cross-sectional data and time series data.
Topic: Data
8. Cross-sectional data are data collected at the same point in time.
TRUE
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 1 Easy
Learning Objective: 01-03 Describe the difference between cross-sectional data and time series data.
Topic: Data
1-2
Copyright © 2017 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of
McGraw-Hill Education.
Bank forPage
Business
2 of 889
Statistics and Analytics in Practice 9th Edition — Bowerman,Page
O’Connell
2 & Murphree, Full Chapters 1–19 ISBN 9781260287844.docx
, Test Bank
Testfor
Bank
Business
for Business
Statistics
Statistics
and Analytics
and Analytics
in Practice
in Practice
9th Edition
9th Edition
— Bowerman,
— Bowerman,
O’Connell
O’Connell
& Murphree,
& Murphree,
Full Chapters
Full Chapters
1–191–19
ISBN 9781260287844.docx
ISBN
2026-03-09
9781260287844
9. Daily temperature in a local community collected over a 30-day time period is an example of
cross-sectional data.
FALSE
Cross-sectional data are collected at the same point in time. This is an example of time series
data.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 1 Easy
Learning Objective: 01-03 Describe the difference between cross-sectional data and time series data.
Topic: Data
10. The number of sick days taken by employees in 2008 for the top 10 technology companies is an
example of time series data.
FALSE
This is an example of cross-sectional data. Time series data are collected at different time
periods.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 1 Easy
Learning Objective: 01-03 Describe the difference between cross-sectional data and time series data.
Topic: Data
11. The number of sick days per month taken by employees for the last 10 years at Apex Co. is an
example of time series data.
TRUE
AACSB: Reflective Thinking Blooms: Understand Difficulty: 2 Medium
Learning Objective: 01-03 Describe the difference between cross-sectional data and time series data.
Topic: Data
12. A quantitative variable can also be referred to as a categorical variable.
FALSE
Qualitative variables are also known as categorical variables.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 1 Easy
Learning Objective: 01-02 Describe the difference between a quantitative variable and a qualitative variable.
Topic: Data
1-3
Copyright © 2017 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of
McGraw-Hill Education.
Bank forPage
Business
3 of 889
Statistics and Analytics in Practice 9th Edition — Bowerman,Page
O’Connell
3 & Murphree, Full Chapters 1–19 ISBN 9781260287844.docx
, Test Bank
Testfor
Bank
Business
for Business
Statistics
Statistics
and Analytics
and Analytics
in Practice
in Practice
9th Edition
9th Edition
— Bowerman,
— Bowerman,
O’Connell
O’Connell
& Murphree,
& Murphree,
Full Chapters
Full Chapters
1–191–19
ISBN 9781260287844.docx
ISBN
2026-03-09
9781260287844
13. In a data set of information on college business students, an example of an element is their
cumulative GPA.
FALSE
The element is college business students. The cumulative GPA is an example of a variable,
which is a characteristic of the element college business students.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 2 Medium
Learning Objective: 01-01 Define a variable.
Topic: Data
14. In an observational study, the variable of interest is called a response variable.
TRUE
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 1 Easy
Learning Objective: 01-05 Identify the different types of data sources: existing data sources, experimental studies, and observational
studies. Topic: Data Sources, Data Warehousing, and Big Data
15. In an experimental study, the aim is to manipulate or set the value of the response variable.
FALSE
In experimental studies, the aim is to manipulate the factor, which is related to the response
variable.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 2 Medium
Learning Objective: 01-05 Identify the different types of data sources: existing data sources, experimental studies, and observational
studies. Topic: Data Sources, Data Warehousing, and Big Data
16. The science of describing the important aspects of a set of measures is called statistical
inference.
FALSE
This is the definition of descriptive statistics. Statistical inference is the science of using a
sample of measurements to make generalizations about the population of measurements.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 2 Medium
Learning Objective: 01-08 Distinguish between descriptive statistics and statistical inference.
Topic: Populations, Samples, and Traditional Statistics
1-4
Copyright © 2017 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of
McGraw-Hill Education.
Bank forPage
Business
4 of 889
Statistics and Analytics in Practice 9th Edition — Bowerman,Page
O’Connell
4 & Murphree, Full Chapters 1–19 ISBN 9781260287844.docx
Testfor
Bank
Business
for Business
Statistics
Statistics
and Analytics
and Analytics
in Practice
in Practice
9th Edition
9th Edition
— Bowerman,
— Bowerman,
O’Connell
O’Connell
& Murphree,
& Murphree,
Full Chapters
Full Chapters
1–191–19
ISBN 9781260287844.docx
ISBN
2026-03-09
9781260287844
Chapter 01 Test Bank Static KEY
1. A population is a set of existing units.
TRUE
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 1 Easy
Learning Objective: 01-07 Describe the difference between a population and a sample.
Topic: Populations, Samples, and Traditional Statistics
2. If we examine some of the population measurements, we are conducting a census of the
population.
FALSE
A census is defined as examining all of the population measurements.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 2 Medium
Learning Objective: 01-07 Describe the difference between a population and a sample.
Topic: Populations, Samples, and Traditional Statistics
3. A random sample is selected so that every element in the population has the same chance of
being included in the sample.
TRUE
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 1 Easy
Learning Objective: 01-09 Explain the concept of random sampling and select a random sample. Topic: Random Sampling, Three Case Studies
That Illustrate Statistical Inference, and Statistical Modeling
4. An example of a quantitative variable is the manufacturer of a car.
FALSE
This is an example of a qualitative or categorical variable.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 1 Easy
Learning Objective: 01-02 Describe the difference between a quantitative variable and a qualitative variable.
Topic: Data
1-1
Copyright © 2017 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of
McGraw-Hill Education.
Bank forPage
Business
1 of 889
Statistics and Analytics in Practice 9th Edition — Bowerman,Page
O’Connell
1 & Murphree, Full Chapters 1–19 ISBN 9781260287844.docx
, Test Bank
Testfor
Bank
Business
for Business
Statistics
Statistics
and Analytics
and Analytics
in Practice
in Practice
9th Edition
9th Edition
— Bowerman,
— Bowerman,
O’Connell
O’Connell
& Murphree,
& Murphree,
Full Chapters
Full Chapters
1–191–19
ISBN 9781260287844.docx
ISBN
2026-03-09
9781260287844
5. An example of a qualitative variable is the mileage of a car.
FALSE
This is an example of a quantitative variable.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 1 Easy
Learning Objective: 01-02 Describe the difference between a quantitative variable and a qualitative variable.
Topic: Data
6. Statistical inference is the science of using a sample of measurements to make generalizations
about the important aspects of a population of measurements.
TRUE
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 2 Medium
Learning Objective: 01-08 Distinguish between descriptive statistics and statistical inference.
Topic: Populations, Samples, and Traditional Statistics
7. Time series data are data collected at the same time period.
FALSE
Time series data are collected over different time periods.
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 1 Easy
Learning Objective: 01-03 Describe the difference between cross-sectional data and time series data.
Topic: Data
8. Cross-sectional data are data collected at the same point in time.
TRUE
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 1 Easy
Learning Objective: 01-03 Describe the difference between cross-sectional data and time series data.
Topic: Data
1-2
Copyright © 2017 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of
McGraw-Hill Education.
Bank forPage
Business
2 of 889
Statistics and Analytics in Practice 9th Edition — Bowerman,Page
O’Connell
2 & Murphree, Full Chapters 1–19 ISBN 9781260287844.docx
, Test Bank
Testfor
Bank
Business
for Business
Statistics
Statistics
and Analytics
and Analytics
in Practice
in Practice
9th Edition
9th Edition
— Bowerman,
— Bowerman,
O’Connell
O’Connell
& Murphree,
& Murphree,
Full Chapters
Full Chapters
1–191–19
ISBN 9781260287844.docx
ISBN
2026-03-09
9781260287844
9. Daily temperature in a local community collected over a 30-day time period is an example of
cross-sectional data.
FALSE
Cross-sectional data are collected at the same point in time. This is an example of time series
data.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 1 Easy
Learning Objective: 01-03 Describe the difference between cross-sectional data and time series data.
Topic: Data
10. The number of sick days taken by employees in 2008 for the top 10 technology companies is an
example of time series data.
FALSE
This is an example of cross-sectional data. Time series data are collected at different time
periods.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 1 Easy
Learning Objective: 01-03 Describe the difference between cross-sectional data and time series data.
Topic: Data
11. The number of sick days per month taken by employees for the last 10 years at Apex Co. is an
example of time series data.
TRUE
AACSB: Reflective Thinking Blooms: Understand Difficulty: 2 Medium
Learning Objective: 01-03 Describe the difference between cross-sectional data and time series data.
Topic: Data
12. A quantitative variable can also be referred to as a categorical variable.
FALSE
Qualitative variables are also known as categorical variables.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 1 Easy
Learning Objective: 01-02 Describe the difference between a quantitative variable and a qualitative variable.
Topic: Data
1-3
Copyright © 2017 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of
McGraw-Hill Education.
Bank forPage
Business
3 of 889
Statistics and Analytics in Practice 9th Edition — Bowerman,Page
O’Connell
3 & Murphree, Full Chapters 1–19 ISBN 9781260287844.docx
, Test Bank
Testfor
Bank
Business
for Business
Statistics
Statistics
and Analytics
and Analytics
in Practice
in Practice
9th Edition
9th Edition
— Bowerman,
— Bowerman,
O’Connell
O’Connell
& Murphree,
& Murphree,
Full Chapters
Full Chapters
1–191–19
ISBN 9781260287844.docx
ISBN
2026-03-09
9781260287844
13. In a data set of information on college business students, an example of an element is their
cumulative GPA.
FALSE
The element is college business students. The cumulative GPA is an example of a variable,
which is a characteristic of the element college business students.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 2 Medium
Learning Objective: 01-01 Define a variable.
Topic: Data
14. In an observational study, the variable of interest is called a response variable.
TRUE
AACSB: Reflective Thinking
Blooms: Remember Difficulty: 1 Easy
Learning Objective: 01-05 Identify the different types of data sources: existing data sources, experimental studies, and observational
studies. Topic: Data Sources, Data Warehousing, and Big Data
15. In an experimental study, the aim is to manipulate or set the value of the response variable.
FALSE
In experimental studies, the aim is to manipulate the factor, which is related to the response
variable.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 2 Medium
Learning Objective: 01-05 Identify the different types of data sources: existing data sources, experimental studies, and observational
studies. Topic: Data Sources, Data Warehousing, and Big Data
16. The science of describing the important aspects of a set of measures is called statistical
inference.
FALSE
This is the definition of descriptive statistics. Statistical inference is the science of using a
sample of measurements to make generalizations about the population of measurements.
AACSB: Reflective Thinking Blooms: Understand Difficulty: 2 Medium
Learning Objective: 01-08 Distinguish between descriptive statistics and statistical inference.
Topic: Populations, Samples, and Traditional Statistics
1-4
Copyright © 2017 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of
McGraw-Hill Education.
Bank forPage
Business
4 of 889
Statistics and Analytics in Practice 9th Edition — Bowerman,Page
O’Connell
4 & Murphree, Full Chapters 1–19 ISBN 9781260287844.docx
