Instructor Manual: Healey, Statistics: A Tool for Social Research and Data Analysis, 12e, 2027, 9798214158556; Chapter 01: Introduction
Instructor Manual
Healey, Statistics: A Tool for Social Research and Data Analysis, 12e, 2027, 9798214158556;
Chapter 01: Introduction
TABLE OF CONTENTS
Purpose and Perspective of the Chapter......................................................................2
Chapter Objectives........................................................................................................2
What’s New in This Chapter........................................................................................2
Chapter Outline.............................................................................................................3
Solutions and Answers for Even-Numbered Problems: Chapter 1.............................6
a
© 2027 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly 1
accessible website, in whole or in part.
, Instructor Manual: Healey, Statistics: A Tool for Social Research and Data Analysis, 12e, 2027, 9798214158556; Chapter 01: Introduction
PURPOSE AND PERSPECTIVE OF THE CHAPTER
The purpose of this chapter is to introduce students to the role of statistics in the research process. The
discussion is guided by the “Wheel of Science” as conceptualized by Walter Wallace. The text always
presents statistics in the context of the research enterprise. That is, statistics are presented as useful tools
for answering sociological questions and testing social science theories, never as ends in themselves.
The chapter also distinguishes between descriptive and inferential statistics and univariate, bivariate, and
multivariate statistics. The distinction between discrete and continuous variables and the concept of level
of measurement is presented in this chapter and the latter is stressed throughout the text as an
organizational device and as a major criterion for selecting statistics appropriately. Exercises are provided
at the end of the chapter for reviewing the characteristics of the three levels of measurement used in this
text.
CHAPTER OBJECTIVES
The following objectives are addressed in this chapter:
1-1 Explain the role of statistics in social research and data analysis.
1-2 Identify the key stages and terms in social scientific research.
1-3 Distinguish between descriptive and inferential statistics.
1-4 Provide examples of discrete and continuous variables.
1-5 Describe three levels of measurement and cite examples of each.
[return to top]
WHAT’S NEW IN THIS CHAPTER
The following elements are improvements in this chapter from the previous edition:
Added guidance on how to adopt a growth mindset to learning about statistics in a section called Do
Statistics Make You Nervous?
Included a new illustration on causal diagrams in Figure 1.1.
Offered new Statistics in Everyday Life box on the 2024 U.S. presidential election.
Created a new Statistics in Everyday Life box on same-sex marriage based on a 2024 Gallup
Poll.
Included a new illustration of discrete and continuous variables in Figure 1.2.
[return to top]
CHAPTER OUTLINE
I. Why Study Statistics?
a
© 2027 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly 2
accessible website, in whole or in part.
, Instructor Manual: Healey, Statistics: A Tool for Social Research and Data Analysis, 12e, 2027, 9798214158556; Chapter 01: Introduction
Statistics help social scientists organize and analyze numerical data to answer questions and test
theories about people and society. They transform raw information into meaningful insights,
enabling informed and evidence-based decisions.
II. Do Statistics Make You Nervous?
Many students feel anxious about learning statistics, but this section reassures them that such
fears are normal and manageable. It encourages adopting a growth mindset, believing that effort
and practice lead to improvement and reminds learners that making mistakes is part of mastering
statistical reasoning.
III. The Role of Statistics in Scientific Inquiry
a. A Journey Through the Scientific Process
i. Theory
Allport’s theory of prejudice, also known as the contact hypothesis, proposes that
prejudice decreases when groups of equal status work cooperatively toward
shared goals, as this promotes personal understanding rather than stereotyping;
however, competition for resources tends to increase prejudice.
ii. Variables and Causation
Allport’s theory explains a causal relationship where equal-status contact
(independent variable) reduces prejudice (dependent variable), showing that
greater cooperative interaction leads to lower bias.
a
© 2027 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly 3
accessible website, in whole or in part.
, Instructor Manual: Healey, Statistics: A Tool for Social Research and Data Analysis, 12e, 2027, 9798214158556; Chapter 01: Introduction
iii. Hypotheses
To test a theory, researchers convert abstract ideas into a specific hypothesis by
clearly defining variables and measurement methods, and then gather data
through systematic observation to compare theory with facts.
iv. Making Observations and Using Data
Testing Allport’s theory involves measuring changes in prejudice after
cooperative or competitive contact, where statistics become essential for
organizing and analyzing data, though their value depends on a well-designed
and conceptually sound research process. To be precise, statistics are crucial and
secondly, the role of statistics is limited since it becomes relevant only at the end
of the observation stage.
v. Empirical Generalizations
Empirical generalizations involve identifying patterns in data; for instance,
noticing that equal-status contact reduces prejudice more for some groups than
others and using these observed trends to refine or expand theories.
vi. A New Theory
When empirical findings lead to theory revision, a new study is conducted to test
the updated idea, continuing the Wheel of Science and gradually deepening
understanding.
vii. Summary: The Dialog Between Theory and Research
The dialog between theory and research highlights that scientific understanding
evolves gradually—theory inspires research, and research refines theory—with
statistics serving as the crucial link that helps analyze data, identify trends, and
improve theoretical explanations.
IV. The Goals of This Text
The goal of this text is to help students understand, apply, and interpret statistics as essential tools
for analyzing social issues, making informed decisions, and appreciating their role in research
and professional practice.
V. Descriptive and Inferential Statistics
a. Descriptive Statistics
Descriptive statistics are methods used to summarize single variables (univariate) or
describe relationships between two or more variables (bivariate or multivariate) through
data reduction and pattern analysis.
i. Univariate Descriptive Statistics
Univariate descriptive statistics use percentages, averages, and graphs to
summarize a single variable, reducing large datasets into a few clear and
meaningful numbers, a process called data reduction.
a
© 2027 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly 4
accessible website, in whole or in part.
Instructor Manual
Healey, Statistics: A Tool for Social Research and Data Analysis, 12e, 2027, 9798214158556;
Chapter 01: Introduction
TABLE OF CONTENTS
Purpose and Perspective of the Chapter......................................................................2
Chapter Objectives........................................................................................................2
What’s New in This Chapter........................................................................................2
Chapter Outline.............................................................................................................3
Solutions and Answers for Even-Numbered Problems: Chapter 1.............................6
a
© 2027 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly 1
accessible website, in whole or in part.
, Instructor Manual: Healey, Statistics: A Tool for Social Research and Data Analysis, 12e, 2027, 9798214158556; Chapter 01: Introduction
PURPOSE AND PERSPECTIVE OF THE CHAPTER
The purpose of this chapter is to introduce students to the role of statistics in the research process. The
discussion is guided by the “Wheel of Science” as conceptualized by Walter Wallace. The text always
presents statistics in the context of the research enterprise. That is, statistics are presented as useful tools
for answering sociological questions and testing social science theories, never as ends in themselves.
The chapter also distinguishes between descriptive and inferential statistics and univariate, bivariate, and
multivariate statistics. The distinction between discrete and continuous variables and the concept of level
of measurement is presented in this chapter and the latter is stressed throughout the text as an
organizational device and as a major criterion for selecting statistics appropriately. Exercises are provided
at the end of the chapter for reviewing the characteristics of the three levels of measurement used in this
text.
CHAPTER OBJECTIVES
The following objectives are addressed in this chapter:
1-1 Explain the role of statistics in social research and data analysis.
1-2 Identify the key stages and terms in social scientific research.
1-3 Distinguish between descriptive and inferential statistics.
1-4 Provide examples of discrete and continuous variables.
1-5 Describe three levels of measurement and cite examples of each.
[return to top]
WHAT’S NEW IN THIS CHAPTER
The following elements are improvements in this chapter from the previous edition:
Added guidance on how to adopt a growth mindset to learning about statistics in a section called Do
Statistics Make You Nervous?
Included a new illustration on causal diagrams in Figure 1.1.
Offered new Statistics in Everyday Life box on the 2024 U.S. presidential election.
Created a new Statistics in Everyday Life box on same-sex marriage based on a 2024 Gallup
Poll.
Included a new illustration of discrete and continuous variables in Figure 1.2.
[return to top]
CHAPTER OUTLINE
I. Why Study Statistics?
a
© 2027 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly 2
accessible website, in whole or in part.
, Instructor Manual: Healey, Statistics: A Tool for Social Research and Data Analysis, 12e, 2027, 9798214158556; Chapter 01: Introduction
Statistics help social scientists organize and analyze numerical data to answer questions and test
theories about people and society. They transform raw information into meaningful insights,
enabling informed and evidence-based decisions.
II. Do Statistics Make You Nervous?
Many students feel anxious about learning statistics, but this section reassures them that such
fears are normal and manageable. It encourages adopting a growth mindset, believing that effort
and practice lead to improvement and reminds learners that making mistakes is part of mastering
statistical reasoning.
III. The Role of Statistics in Scientific Inquiry
a. A Journey Through the Scientific Process
i. Theory
Allport’s theory of prejudice, also known as the contact hypothesis, proposes that
prejudice decreases when groups of equal status work cooperatively toward
shared goals, as this promotes personal understanding rather than stereotyping;
however, competition for resources tends to increase prejudice.
ii. Variables and Causation
Allport’s theory explains a causal relationship where equal-status contact
(independent variable) reduces prejudice (dependent variable), showing that
greater cooperative interaction leads to lower bias.
a
© 2027 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly 3
accessible website, in whole or in part.
, Instructor Manual: Healey, Statistics: A Tool for Social Research and Data Analysis, 12e, 2027, 9798214158556; Chapter 01: Introduction
iii. Hypotheses
To test a theory, researchers convert abstract ideas into a specific hypothesis by
clearly defining variables and measurement methods, and then gather data
through systematic observation to compare theory with facts.
iv. Making Observations and Using Data
Testing Allport’s theory involves measuring changes in prejudice after
cooperative or competitive contact, where statistics become essential for
organizing and analyzing data, though their value depends on a well-designed
and conceptually sound research process. To be precise, statistics are crucial and
secondly, the role of statistics is limited since it becomes relevant only at the end
of the observation stage.
v. Empirical Generalizations
Empirical generalizations involve identifying patterns in data; for instance,
noticing that equal-status contact reduces prejudice more for some groups than
others and using these observed trends to refine or expand theories.
vi. A New Theory
When empirical findings lead to theory revision, a new study is conducted to test
the updated idea, continuing the Wheel of Science and gradually deepening
understanding.
vii. Summary: The Dialog Between Theory and Research
The dialog between theory and research highlights that scientific understanding
evolves gradually—theory inspires research, and research refines theory—with
statistics serving as the crucial link that helps analyze data, identify trends, and
improve theoretical explanations.
IV. The Goals of This Text
The goal of this text is to help students understand, apply, and interpret statistics as essential tools
for analyzing social issues, making informed decisions, and appreciating their role in research
and professional practice.
V. Descriptive and Inferential Statistics
a. Descriptive Statistics
Descriptive statistics are methods used to summarize single variables (univariate) or
describe relationships between two or more variables (bivariate or multivariate) through
data reduction and pattern analysis.
i. Univariate Descriptive Statistics
Univariate descriptive statistics use percentages, averages, and graphs to
summarize a single variable, reducing large datasets into a few clear and
meaningful numbers, a process called data reduction.
a
© 2027 Cengage Learning, Inc. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly 4
accessible website, in whole or in part.
