You are here

Making Sense of Numbers

Making Sense of Numbers teaches students the skills they need to be both consumers and producers of quantitative research: able to read about, collect, calculate, and communicate numeric information for both everyday tasks and school or work assignments. The text teaches how to avoid making common errors of reasoning, calculation, or interpretation by introducing a systematic approach to working with numbers, showing students how to figure out what a particular number means. The text also demonstrates why it is important to apply a healthy dose of skepticism to the numbers we all encounter, so that we can understand how those numbers can (and cannot) be interpreted in their real-world context. Jane E. Miller uses annotated examples on a wide variety of topics to illustrate how to use new terms, concepts, and approaches to working with numbers. End-of-chapter engagement activities designed based on Miller’s three decades of teaching experience can be used in class or as homework assignments, with some for students to do individually and others intended for group discussion. The book is ideally suited for a range of courses, including quantitative reasoning, research methods, basic statistics, data analysis, and communicating quantitative information.

An instructor website for the book at includes a test bank, editable PowerPoint slides, and tables and figures from the book.

List of Figures
List of Tables
About the Author
Chapter 1: Introduction to Making Sense of Numbers
The Many Uses of Numbers

Common Tasks Involving Numbers

Plausibility of Numeric Values

Challenges in Making Sense of Numbers

How We Learn to Make Sense of Numbers

Chapter 2: Foundational Concepts for Quantitative Research
Terminology for Quantitative Research

The Research Circle

Goals Of Quantitative Research

The W’s

Report and Interpret Numbers

Specify Direction and Magnitude

Chapter 3: Topic and Conceptualization

Scope of a Definition

How Topic and Scope Affect Plausibility

How Topic and Perspective Affect Optimal Values

Chapter 4: Measurement

Factors Affecting Operationalization

Levels of Measurement


Data Collection and Level of Measurement

How Measurement Affects Plausibility

Reliability and Validity of Numeric Measures

Chapter 5: Context
What Is Context?

How Context Affects Plausibility

How Context Affects Measurement

Population Versus Study Sample



Level of Analysis and Fallacy of Level

Chapter 6: Working With Tables
Criteria for Effective Tables

Anatomy of a Table

Organizing Data in Tables and Charts

Reading Data From Tables

Considerations for Creating Tables

Chapter 7: Working With Charts and Visualizations
Criteria for Effective Charts and Visualizations

Visual Perception Principles

Anatomy of a Chart or Visualization

Charts and Visualizations for Specific Tasks

Design Issues

Common Errors in Chart Creation

Chapter 8: Comparison Values, Contrast Sizes, and Standards
Reference Groups and Comparison Values

Standards, Thresholds, and Target Values

Contrast Sizes for Quantitative Variables

Considerations for Comparability

Chapter 9: Numbers, Comparisons, and Calculations
Numeric Measures of Level

Plausibility Criteria for Measures of Level

Measures of Position in a Ranked List

Plausibility Criteria for Measures of Position

Mathematical Calculations

Plausibility Criteria for Results of Calculations

How Level of Measurement Affects Valid Types of Comparison

Choosing Types of Comparisons

Chapter 10: Distributions and Associations
Distributions of Single Variables

Plausibility Criteria for Univariate Statistics

Tables and Charts for Presenting Distributions

Associations Between Two or More Variables

Three-Way Associations

Plausibility Criteria for Bivariate and Three-Way Statistics

Comparisons by Level of Measurement, Revisited

Chapter 11: Bias
What Is Bias?

Time Structure of Study Designs

Sampling Methods

Study Nonresponse

Item Nonresponse

Measurement Bias

Data Sources

Chapter 12: Causality
Causality Defined

Criteria for Assessing Causality

Experimental Studies

Observational Studies

Research Strategies for Assessing Confounding

Random Sampling vs. Random Assignment

Implications of Causality for Quantitative Research

Chapter 13: Uncertainty of Numeric Estimates
What Is Statistical Uncertainty?

Inferential Statistics

Measures of Uncertainty

Uncertainty vs. Bias

Basics of Hypothesis Testing

Drawbacks of Traditional Hypothesis Testing

Interpreting Inferential Statistics for Bivariate and Three-Way Procedures

Chapter 14: Communicating Quantitative Research
Tools for Presenting Quantitative Research

Expository Writing Techniques

Writing About Numbers in Particular

Conveying the Type of Measure or Calculation

Writing About Distributions

Writing About Associations

Writing About Complex Patterns

Content and Structure of Research Formats

Chapter 15: The Role of Research Methods in Making Sense of Numbers
The W’s Revisited

Practical Importance

Importance of a Numeric Finding: The Big Picture

How Study Design, Measurement, and Sample Size Affect “Importance”

Making Sense of Numbers in Quantitative Research Tasks

Appendix A: Why and How to Create New Variables
Why New Variables Might Be Needed

Transformations of Numbers

Indexes and Scales

New Continuous Variables

New Categorical Variables

Appendix B: Sampling Weights
The Purpose of Sampling Weights

Sampling Weights for Disproportionate Sampling

Communicating Use of Sampling Weights

Appendix C: Brief Technical Background on Inferential Statistics
Standard Error and Sample Size

Margin of Error

Confidence Interval

Criteria for Making Sense of Measures of Uncertainty

Hypothesis Testing

Errors in Hypothesis Testing

Plausibility Criteria for Inferential Test Statistics



Instructor Resource Site

For additional information, custom options, or to request a personalized walkthrough of these resources, please contact your sales representative.

LMS cartridge included with this title for use in Blackboard, Canvas, Brightspace by Desire2Learn (D2L), and Moodle

The LMS cartridge makes it easy to import this title’s instructor resources into your learning management system (LMS). These resources include:

  • Test banks
  • Editable chapter-specific PowerPoint® slides
  • All tables and figures from the textbook 
Don’t use an LMS platform?

You can still access all of the same online resources for this title via the password-protected Instructor Resource Site.

This text invites students to develop an in-depth understanding of core concepts in research methods, clearly guides them through real-life examples, and offers tools needed for the development of strong analytical skills highly valued in the labor market.

Maria Aysa-Lastra
Winthrop University

This an incredibly useful textbook, showing students how to interpret others’ quantitative research, think about quantitative research of their own, and communicate the findings of that research. I learned several great tips myself on writing effectively about quantitative research findings!

Susan A. Dumais
Lehman College, CUNY

Making Sense of Numbers is an excellent companion for those learning to navigate the world of quantitative research.

Marc Isaacson
Augsburg University

The entire USG system has moved toward open-access resource implementation (via the following language):

Open Access:
is information that is:
Free to read
is a movement that wants to increase information access and innovation.
usually refers to open access publishing, particularly of scholarly communication in academia.
may be an answer to the serials / scholarly communication crisis, which refers to the system where information is locked up in subscription journals and databases whose prices keep rising (as library and university budgets stagnate or decrease) and universities and libraries are forced to pay for the creation of the research as well as to buy it back through subscriptions.
is about the democratization of information and knowledge.
is carried out largely through open access journals, subject specific and institutional repositories, where research is posted online for anyone to access. These are indexed by Google and other search engines increasing visibility and impact of the research.

Dr Natasha N. Johnson
Criminal Justice Dept, Georgia State University
September 30, 2022
Key features
  • Annotated Examples, which include new terms, concepts and approaches, help students understanding of the material.
  • Engagement Activities at the ends of chapters, which can be used in class or as homework assignments, with some for students to do individually and others intended for groups discussion.