Sandlot Stats
eBook - ePub

Sandlot Stats

Learning Statistics with Baseball

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Sandlot Stats

Learning Statistics with Baseball

About this book

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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Yes, you can access Sandlot Stats by Stanley Rothman in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Table of contents

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