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Pub. Date:
Johns Hopkins University Press
Pub. Date:
Johns Hopkins University Press
Sandlot Stats: Learning Statistics with Baseball

Sandlot Stats: Learning Statistics with Baseball

by Stanley Rothman Stanley Rothman
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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.

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Product Details

ISBN-13: 9781421406022
Publisher: Johns Hopkins University Press
Publication date: 11/01/2012
Edition description: New Edition
Pages: 592
Product dimensions: 10.10(w) x 7.20(h) x 1.60(d)
Age Range: 18 Years

About the Author

Stanley Rothman is professor of mathematics at Quinnipiac University.

Table of Contents

Acknowledgments ix

List of Abbreviations xi

Introduction 1

Chapter 1 Basic Statistical Definitions 8

Chapter 2 Descriptive Statistics for One Quantitative Variable 38

Chapter 3 Descriptive Measures Used in Baseball 84

Chapter 4 Comparing Two Quantitative Data Sets 117

Chapter 5 Linear Regression and Correlation Analysis for Two Quantitative Variables 145

Chapter 6 Descriptive Statistics Applied to Qualitative Variables 177

Chapter 7 Probability 190

Chapter 8 Sports Betting 225

Chapter 9 Baseball and Traditional Descriptive Measures 237

Chapter 10 Final Comparison of Batting Performance between Aaron and Bonds 245

Chapter 11 Probability Distribution Functions for a Discrete Random Variable 267

Chapter 12 Probability Density Functions for a Continuous Variable 291

Chapter 13 Sampling Distributions 308

Chapter 14 Confidence Intervals 330

Chapter 15 Hypothesis Testing for One Population 366

Chapter 16 Streaking 398

Chapter 17 Mission Impossible: Batting 400 for a Season 439

Chapter 18 Postseason 505

Appendix A Hypothesis Testing for Two Population Proportions 535

Appendix B The Chi-Square Distribution 543

Appendix C Statistical Tables 553

Index 561

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