Sandlot stats : learning statistics with baseball
著者
書誌事項
Sandlot stats : learning statistics with baseball
Johns Hopkins University Press, c2012
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注記
Includes index
内容説明・目次
内容説明
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.
目次
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
「Nielsen BookData」 より