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summary
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 distributionSandlot 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.

Table of Contents

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  1. Cover
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  1. Title Page, Copyright Page
  2. pp. i-vi
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  1. Contents
  2. pp. vii-viii
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  1. Acknowledgments
  2. pp. ix-x
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  1. List of Abbreviations
  2. pp. xi-xiv
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  1. Introduction
  2. pp. 1-7
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  1. Chapter 1. Basic Statistical Definitions
  2. pp. 8-37
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  1. Chapter 2. Descriptive Statistics for One Quantitative Variable
  2. pp. 38-83
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  1. Chapter 3. Descriptive Measures Used in Baseball
  2. pp. 84-116
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  1. Chapter 4. Comparing Two Quantitative Data Sets
  2. pp. 117-144
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  1. Chapter 5. Linear Regression and Correlation Analysis for Two Quantitative Variables
  2. pp. 145-176
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  1. Chapter 6. Descriptive Statistics Applied to Qualitative Variables
  2. pp. 177-189
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  1. Chapter 7. Probability
  2. pp. 190-224
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  1. Chapter 8. Sports Betting
  2. pp. 225-236
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  1. Chapter 9. Baseball and Traditional Descriptive Measures
  2. pp. 237-244
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  1. Chapter 10. Final Comparison of Batting Performance between Aaron and Bonds
  2. pp. 245-266
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  1. Chapter 11. Probability Distribution Functions for a Discrete Random Variable
  2. pp. 267-290
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  1. Chapter 12. Probability Density Functions for a Continuous Variable
  2. pp. 291-307
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  1. Chapter 13. Sampling Distributions
  2. pp. 308-329
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  1. Chapter 14. Confidence Intervals
  2. pp. 330-365
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  1. Chapter 15. Hypothesis Testing for One Population
  2. pp. 366-397
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  1. Chapter 16. Streaking
  2. pp. 398-438
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  1. Chapter 17. Mission Impossible: Batting .400 for a Season
  2. pp. 439-504
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  1. Chapter 18. Postseason
  2. pp. 505-534
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  1. Appendix A. Hypothesis Testing for Two Population Proportions
  2. pp. 535-542
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  1. Appendix B. The Chi-Square Distribution
  2. pp. 543-552
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  1. Appendix C. Statistical Tables
  2. pp. 553-560
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  1. Index
  2. pp. 561-571
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