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Table of Contents

About the Authors

Preface

Chapter 1: Testing Claims in Sports

Is Steph Curry a Streaky Shooter?

• Section 1: Modeling Athletic Performance

• Section 1 Exercises

• Section 2: Simulating Athletic Performance

• Section 2 Exercises

• Section 3: Other Applications (It's not just sports)

• Section 3 Exercises

• Chapter 1 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 1 Investigative Project

Chapter 2: Analyzing Categorical Variables

Did Cam Newton Choke in the Super Bowl?

• Section 1: Displaying Categorical Data

• Section 1 Exercises

• Section 2: Tests for a Single Percentage

• Section 2 Exercises

• Section 3: Simulating with Technology and the State-Simulate-Conclude Process

• Section 3 Exercises

• Section 4: Other Applications (It's not just sports)

• Section 4 Exercises

• Chapter 2 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 2 Investigative Project

Chapter 3: Comparing Two Percentages

Do NFL Teams have a Home-Field Advantage?

• Section 1: Summarizing Relationships between Two Categorical Variables

• Section 1 Exercises

• Section 2: Tests for a Difference in Percentages

• Section 2 Exercises

• Section 3: Simulating with Technology and the State-Simulate-Conclude Process

• Section 3 Exercises

• Section 4: Other Applications (It's not just sports)

• Section 4 Exercises

• Chapter 3 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 3 Investigative Project

Chapter 4: Experiments

Can You Visualize Success?

• Section 1: Experiments and Observational Studies

• Section 1 Exercises

• Section 2: Designing Experiments

• Section 2 Exercises

• Section 3: Analyzing Experiments with Two Categorical Variables

• Section 3 Exercises

• Section 4: Type I and Type II Errors

• Section 4 Exercises

• Section 5: Other Applications (It's not just sports)

• Section 5 Exercises

• Chapter 4 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 4 Investigative Project

Chapter 5: Conditional Probability and Strategy in Sports

Should You Go for It on Fourth Down?

• Section 1: Probability and Two-Way Tables

• Section 1 Exercises

• Section 2: Conditional Probability and Independence

• Section 2 Exercises

• Section 3: Tree Diagrams and Multiplication Rules

• Section 3 Exercises

• Section 4: Win Probability and Strategy in Sports

• Section 4 Exercises

• Section 5: Other Applications (It's not just sports)

• Section 5 Exercises

• Chapter 5 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 5 Investigative Project

Chapter 6: Analyzing Quantitative Variables

Do Rested Teams Play Better Defense?

• Section 1: Displaying Quantitative Data

• Section 1 Exercises

• Section 2: Measuring Center and Variability

• Section 2 Exercises

• Section 3: Outliers and Boxplots

• Section 3 Exercises

• Section 4: Other Applications (It's not just sports)

• Section 4 Exercises

• Chapter 6 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 6 Investigative Project

Chapter 7: Comparing Two Means or Medians

Do Sports Drinks Keep You Hydrated?

• Section 1: Tests for a Difference Between Two Means

• Section 1 Exercises

• Section 2: Technology and the State-Simulate-Conclude Process

• Section 2 Exercises

• Section 3: Tests for a Difference Between Two Medians

• Section 3 Exercises

• Section 4: Other Applications (It's not just sports)

• Section 4 Exercises

• Chapter 7 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 7 Investigative Project

Chapter 8: Exploring Paired Data

Can a swimsuit make you faster?

• Section 1: Analyzing Paired Data

• Section 1 Exercises

• Section 2: Tests for a Mean Difference

• Section 2 Exercises

• Section 3: Technology and the State-Simulate-Conclude Process

• Section 3 Exercises

• Section 4: Other Applications (It's not just sports)

• Section 4 Exercises

• Chapter 8 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 8 Investigative Project

Chapter 9: More Measures of Variability

Which 7-Iron is More Consistent?

• Section 1: Measuring Variability with the Mean Absolute Deviation

• Section 1 Exercises

• Section 2: Measuring Variability with the Standard Deviation

• Section 2 Exercises

• Section 3: Tests for a for a Difference in Two Standard Deviations

• Section 3 Exercises

• Section 4: Other Applications (It's not just sports)

• Section 4 Exercises

• Chapter 9 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 9 Investigative Project

Chapter 10: Standardized Scores and Normal Distributions

Who Should I Draft for my Fantasy Baseball Team?

• Section 1: Standardized Scores (z-scores)

• Section 1 Exercises

• Section 2: Normal Distributions and the 68-95-99.7 Rule

• Section 2 Exercises

• Section 3: Normal Distribution Calculations

• Section 3 Exercises

• Section 4: Other Applications (It's not just sports)

• Section 4 Exercises

• Chapter 10 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 10 Investigative Project

Chapter 11: Sampling with Confidence

What is America's Favorite Sport to Watch?

• Section 1: Sampling and Bias

• Section 1 Exercises

• Section 2: Sampling Variability and Confidence Intervals

• Section 2 Exercises

• Section 3: Estimating ABILITY with Confidence Intervals

• Section 3 Exercises

• Section 4: Other Applications (It's not just sports)

• Section 4 Exercises

• Chapter 11 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 11 Investigative Project

Chapter 12: Relationships between Two Quantitative Variables

Teeing Off: Hit it Long or Hit it Straight?

• Section 1: Displaying Relationships

• Section 1 Exercises

• Section 2: Correlation

• Section 2 Exercises

• Section 3: Testing the Correlation

• Section 3 Exercises

• Section 4: Other Applications (It's not just sports)

• Section 5 Exercises

• Chapter 12 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 12 Investigative Project

Chapter 13: Using Relationships to Make Predictions

How Can We Build a Better Baseball Team?

• Section 1: Predictions and Residuals

• Section 1 Exercises

• Section 2: Least-Squares Regression Lines

• Section 2 Exercises

• Section 3: Assessing a Least-Squares Regression Line

• Section 3 Exercises

• Section 4: Regression to the Mean

• Section 4 Exercises

• Section 5: Other Applications (It's not just sports)

• Section 5 Exercises

• Chapter 13 Summary

• What Did You Learn?
• Chapter Review Exercises
• Chapter 13 Investigative Project

Authors

Josh Tabor

Josh Tabor has enjoyed teaching Introductory and AP® Statistics for more than 26 years. He received a BS in mathematics from Biola University, in La Mirada, California. In recognition of his outstanding work as an educator, Josh was named one of five finalists for Arizona Teacher of the Year in 2011. He is a past member of the AP® Statistics Development Committee (2005–2009), as well as an experienced Table Leader, Question Leader, and Exam Leader at the AP® Statistics Reading. In 2013, Josh was named to the SAT® Mathematics Development Committee. Josh is a member of the American Statistical Association (ASA) and was a reviewer for the ASA’s Pre-K–12 Guidelines for Assessment and Instruction in Statistics Education II (GAISE II). Each year, Josh leads many workshops and frequently speaks at local, national, and international conferences. In addition to teaching and speaking, he has authored articles in The American Statistician, The Mathematics Teacher, STATS Magazine, and The Journal of Statistics Education. Josh is coauthor of The Practice of Statistics (now in its seventh edition), the best-selling textbook for AP® Statistics, and of Statistics and Probability with Applications (now in its fourth edition), a popular choice for high school introductory statistics. Combining his love of statistics and sports, Josh teamed with Christine Franklin to write Statistical Reasoning in Sports, an innovative textbook for statistical literacy courses. Outside of work, Josh enjoys gardening, traveling, and playing board games with his family.

Chris Franklin

Christine (Chris) Franklin is the K–12 Statistics Ambassador for the American Statistical Association and an elected ASA Fellow. Now retired from the University of Georgia as the Lothar Tresp Honoratus Honors Professor and Senior Lecturer Emerita in Statistics, she is also the coauthor of an Introductory Statistics textbook published with Pearson and has published more than 60 journal articles and book chapters. Chris was the lead writer for the groundbreaking document of the American Statistical Association Pre-K–12 Guidelines for the Assessment and Instruction in Statistics Education (GAISE) Framework and chaired the writing team of the ASA Statistical Education of Teachers (SET) report. She is a past Chief Reader for Advanced Placement® Statistics, a Fulbright scholar to New Zealand (2015), recipient of the United States Conference on Teaching Statistics (USCOTS) Lifetime Achievement Award and the prestigious ASA Founder’s Award, and is an elected member of the International Statistical Institute (ISI). Chris loves being with her family, running, hiking, scoring baseball games, and reading mysteries.

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