Statistics With Humans demystifies statistics for the social and behavioral sciences. Author Katie Jacobs combines relatable examples, a conversational approach, and vibrant visuals to win over even math-averse students. Guiding learners from foundational concepts to more complex analyses, the book includes SPSS instruction, making it an accessible and practical way to help students see the importance of statistics.
Also available in Sage Vantage, an intuitive learning platform that integrates quality Sage textbook content with assignable multimedia activities and auto-graded assessments to drive student engagement and ensure accountability. Learn more about ISBN 978-1-0718-9108-7, Statistics With Humans - Vantage Digital Option.
Arvustused
An excellent text for any undergraduate research methods and statistics course in the social sciences. This text provides precise methodology, thorough analysis and concise explanation of both descriptive and inferential statistics in an easy to read format. -- John Gulledge Jacobs approaches statistics from a student-centered perspective. It is clear in the language used, examples given, and general
approach that she is passionate about statistics and wants to share that with her students! -- Megan Raddatz Jacobs does a great job explaining statistics in an easy to understand conversational manner. I strongly recommend this book. -- Amanda Harmon An original text with detailed quality information, step-by-step procedures, and visually rich examples for statistics students! -- Nicole Hamilton This is an in-depth look at the assumptions, calculations, and examples of different statistical tests. After reading, students will gain insight into why and how to use these to explore various research questions. -- Sara L. Bagley The deep examples and explanations are great ways to increase the understanding of the material. -- George S. Robinson
Preface
About the Authors
Part 1: Welcome to Statistics Boot Camp
Chapter 1: May I Make an Introduction? To Statistics, That Is
A Brief Introduction to Statistics
Statistics Is All About Data
Descriptive and Inferential Statistics
Sampling
Measurement
Research Methods Fundamentals
Basic Research Designs
SPSS Bonus Content Unlocked: Setting Up SPSS Data Files
Summary
Symbol Guide
Terms to Know
Putting in The Work
Chapter 2: Measures of Central Tendency: Attraction
An Introduction to Descriptive Statistics
Mean
Mode
Median
Calculating Measures of Central Tendency for Data on a Nominal Level of
Measurement
Calculating Measures of Central Tendency for Data on an Ordinal Level of
Measurement
Calculating Measures of Central Tendency for Data on a Scale With an
Outlier in the Data Set
SPSS Bonus Content Unlocked: Finding Measures of Central Tendency
Summary
Symbol Guide
Formulas
Terms to Know
Putting in the Work
Chapter 3: Measures of Variability: Tree Branches Scattered Across the Sky
A Brief Introduction to Measures of Variability
Range
Introduction to Mean Absolute Deviation, Variance, and Standard Deviation
Mean Absolute Deviation
The Population Variance
Population Standard Deviation
The Unbiased Estimate
SPSS Bonus Content Unlocked: Finding Measures of Variability
Summary
Symbol Guide
Formulas
Terms to Know
Putting in The Work
Chapter 4: Visual Displays and Measures of Distribution: Lets Lay It All
Out
A Brief Introduction to Measures of Distribution
Ungrouped Frequency Distribution Tables
Cumulative Frequency Distribution Tables
Grouped Frequency Distribution Tables
Histograms
Common Distribution Shapes
Skewness
Kurtosis
SPSS Bonus Content Unlocked
Summary
Symbol Guide
Formulas
Terms to Know
Putting in The Work
Chapter 5: The Standard Normal Distribution: Finding Order in the Chaos
A Brief Introduction to Relative Frequency Histograms
All About Density Curves
Starring the Normal Curve
Calculating Standardized Scores
Using z-Scores to Identify Outliers
Standard Normal Distribution
Area Under the Curve
SPSS Bonus Content Unlocked: Calculating z-Scores
Summary
Symbol Guide
Formulas
Terms to Know
Putting in the Work
Chapter 6: Probability and Sampling: Its More Than Sports and Gambling
An Introduction to Probability
The Probability of The Union of Events
The Probability of The Intersection of Events
Sample Spaces
The Probability of Binomial Experiments
The Probability of Continuous Data
Summary
Symbol Guide
Formulas
Terms to Know
Putting in the Work
Part 2: Welcome to Inferential Statistics
Chapter 7: Hypothesis Testing and Statistical Significance: Putting It
Altogether
A Brief Introduction to the Hypothesis Testing Steps
Step 1: Determine Which Statistical Analysis to Use
Step 2: Write the Research and Null Hypotheses
Step 3: Check the Assumptions
Step 4: Calculate the Test Statistic
Step 5: Find the Critical Value(s)
Step 6: Make a Decision
Step 7: Conduct Relevant Follow-Up Analyses
Summary
Symbol Guide
Formulas
Terms to Know
Putting in the Work
Chapter 8: One-Sample z-Test: Are NBA Players Taller Than the Average Male?
Step 1: Decide Which Statistical Analysis to Use
Step 2: Write the Research and Null Hypotheses
Step 3: Check the Assumptions
Step 4: Calculate the Test Statistic
Step 5: Find the Critical Value(s)
Step 6: Make a Decision
Step 7: Conduct Relevant Follow-Up Analyses
Summary
Symbol Guide
Formulas
Terms to Know
Putting in the Work
Chapter 9: Independent Samples t-Test: Who Owns More Shoes?
Step 1: Determine Which Statistical Analysis to Use
Step 2: Write the Research and Null Hypotheses
Step 3: Check the Assumptions
Step 4: Calculate the Test Statistic
Step 5: Find the Critical Value(s)
Step 6: Make a Decision
Step 7: Conduct Relevant Follow-Up Analyses
SPSS Bonus Content Unlocked: Running the Independent Samples t-Test
Summary
Symbol Guide
Formulas
Terms to Know
Putting in the Work
Chapter 10: Dependent Samples t-Test: Does Dry January Actually Work?
Step 1: Determine Which Statistical Analysis to Use
Step 2: Write the Research and Null Hypotheses
Step 3: Check the Assumptions
Step 4: Calculate the Test Statistic
Step 5: Find the Critical Value(s)
Step 6: Make a Decision
Step 7: Conduct Relevant Follow-Up Analyses
SPSS Bonus Content Unlocked: Running the Dependent Samples t-Test
Summary
Symbol Guide
Formulas
Terms to Know
Putting in the Work
Chapter 11: One-Way ANOVA: Who is the Biggest Diva?
Step 1: Determine Which Statistical Analysis to Use
Step 2: Write the Research and Null Hypotheses
Step 3: Check the Assumptions
Step 4: Calculate the Test Statistic
Step 5: Find the Critical Values
Step 6: Make a Decision
Step 7: Conduct Relevant Follow-Up Analyses
SPSS Bonus Content Unlocked: Running the One-Way ANOVA
Summary
Symbol Guide
Formulas
Terms to Know
Putting in the Work
Chapter 12: The Pearson Product-Moment Correlation: Are TikTok and Reading
Times Related?
Step 1: Determine Which Statistical Analysis to Use
Step 2: Write the Research and Null Hypotheses
Step 3: Check the Assumptions
Step 4: Calculate the Test Statistic
Step 5: Find the Critical Value(s)
Step 6: Make a Decision
Step 7: Conduct Relevant Follow-Up Analyses
SPSS Bonus Content Unlocked: Running the Pearson Product-Moment
Correlation
Summary
Symbol Guide
Formulas
Terms to Know
Putting in the Work
Chapter 13: Simple Linear Regression: Does Time on Dating Apps Predict Dating
Bitterness?
Introduction to Regression
Step 1: Determine Which Statistical Analysis to Use
Step 2: Write the Research and Null Hypotheses
Step 3: Check the Assumptions
Step 4: Calculate the Test Statistic
Step 5: Find the Critical Values
Step 6: Make a Decision
Step 7: Conduct Relevant Follow-Up Analyses
SPSS Bonus Content Unlocked: Running Simple Linear Regression
Summary
Symbol Guide
Formulas
Terms to Know
Putting in the Work
Part 3: Welcome to Nonparametric Analyses
Chapter 14: Chi-square Goodness-of-Fit test: Are People Terrified by AI More
Than Youd Expect?
Introduction to Non-Parametric Analyses
Step 1: Determine Which Statistical Analysis to Use
Step 2: Write the Research and Null Hypotheses
Step 3: Check the Assumptions
Step 4: Calculate the Test Statistic
Step 5: Find the Critical Value
SPSS Bonus Content Unlocked: Running the Chi-Square Goodness-of-Fit Test
Summary
Symbol Guide
Formulas
Terms to Know
Putting in The Work
Appendix A: Standard Normal Distribution Table (i.e. z Critical Value Table)
Appendix B: Students t Distribution Table (t_CV Table)
Appendix C: F Distribution Table (F_CV Table)
Appendix D: Studentized Range q Table
Appendix E: Pearson Product-Moment Correlation Critical Value Table (r_CV
Table)
Appendix F: Chi-Square Critical Value Table (X^2_CV Table)
Dr. Katie Jacobs is a Professor of Psychological Science at the University of Central Missouri, where she teaches lifespan development, statistics, and research methods. Since 2014, she has directed the Advancement of Mental Health Lab, which focuses on destigmatizing mental illness and increasing access to evidence-based mental health care at low to no cost. Her lab has presented both domestically and internationally.
She is committed to providing authentic, service-based, and global learning opportunities. In 2025, she served as the faculty representative for UCMs inaugural Global Vision Scholarship Program trip to Puerto Rico, and in 2024 she was a faculty leader for a Costa Rica faculty-led tour examining comparative health-care systems.
Dr. Jacobs has served as the President (2016-2018) and Vice President (2015-2016) of UCMs Faculty Senate, as well as Vice President of the Missouri Association of Faculty Senate (2017-2018). Her awards include the CHST Excellence in Service Award, the UCM Undergraduate Research Mentor of the Year, and Honors College Faculty Fellow. Her current projects include the 2026 release of Statistics With Humans with Sage Publications and The Things We Dont Talk About mental health campaign.
Photo credit: Nathan Jacobs and Amanda Knight
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