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# Sandlot Stats

Learning Statistics with Baseball

Stanley Rothman

Publication Date

Sandlot Stats uses the national pastime to help students who love baseball learn—and enjoy—statistics.

As Derek Jeter strolls toward the plate, the announcer tosses out a smattering of statistics—from hitting streaks to batting averages. But what do the numbers mean? And how can America’s favorite pastime be a model for learning about statistics? Sandlot Stats is an innovative textbook that explains the mathematical underpinnings of baseball so that students can understand the world of statistics and probability.

Carefully illustrated and filled with exercises and examples, this book teaches...

Sandlot Stats uses the national pastime to help students who love baseball learn—and enjoy—statistics.

As Derek Jeter strolls toward the plate, the announcer tosses out a smattering of statistics—from hitting streaks to batting averages. But what do the numbers mean? And how can America’s favorite pastime be a model for learning about statistics? Sandlot Stats is an innovative textbook that explains the mathematical underpinnings of baseball so that students can understand the world of statistics and probability.

Carefully illustrated and filled with exercises and examples, this book teaches the fundamentals of probability and statistics through the feats of baseball legends such as Hank Aaron, Joe DiMaggio, and Ted Williams—and more recent players such as Barry Bonds, Albert Pujols, and Alex Rodriguez. Exercises require only pen-and-paper or Microsoft Excel to perform the analyses.

Sandlot Stats covers all the bases, including
• descriptive and inferential statistics
• linear regression and correlation
• probability
• sports betting
• probability distribution functions
• sampling distributions
• hypothesis testing
• confidence intervals
• chi-square distribution

Sandlot Stats offers information covered in most introductory statistics books, yet is peppered with interesting facts from the history of baseball to enhance the interest of the student and make learning fun.

Reviews

## Reviews

Sandlot Stats served as an instrumental and informative piece to the Baseball Statistics course. The amount of time and tedious effort put into the project is evident, as this book is absolutely packed with information. The book puts a new spin on mathematics, and makes it more understandable for even the most casual of baseball fans. Baseball purists and sabermetric geeks alike will love this book.

Dr. Rothman has hit a 'home run.' Sandlot Stats: Learning Statistics with Baseball is not only a fine book to read, but a text which can also serve as an excellent resource book.

For those interested in this subject—this is your book.

If this had been the textbook for a basic statistics course that I took as a student, I might have remembered that course forever as the best class I ever had.

Sandlot Stats is a readable and resourceful introductory textbook for statistics.

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## Book Details

Publication Date
Status
Available
Trim Size
7
x
10
Pages
592
ISBN
9781421406022
Illustration Description
190 line drawings
Subject

Acknowledgments
List of Abbreviations
Introduction
1. Basic Statistical Definitions
2. Descriptive Statistics for One Quantitative Variable
3. Descriptive Measures Used in Baseball
4. Comparing Two

Acknowledgments
List of Abbreviations
Introduction
1. Basic Statistical Definitions
2. Descriptive Statistics for One Quantitative Variable
3. Descriptive Measures Used in Baseball
4. Comparing Two Quantitative Data Sets
5. Linear Regression and Correlation Analysis for Two Quantitative Variables
6. Descriptive Statistics Applied to Qualitative Variables
7. Probability
8. Sports Betting
9. Baseball and Traditional Descriptive Measures
10. Final Comparison of Batting Performance between Aaron and Bonds
11. Probability Distribution Functions for a Discrete Random Variable
12. Probability Density Functions for a Continuous Variable
13. Sampling Distributions
14. Confidence Intervals
15. Hypothesis Testing for One Population
16. Streaking
17. Mission Impossible: Batting.400 for a Season
18. Postseason
Appendix A: Hypothesis Testing for Two Population Proportions
Appendix B: The Chi-Square Distribution
Appendix C: Statistical Tables
Index

Author Bio
Featured Contributor

## Stanley Rothman, Ph.D.

Stanley Rothman is professor of mathematics at Quinnipiac University.
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