What is a P-value anyway? 34 stories to help you actually understand statistics

Andrew Vickers, 1967-

Book - 2010

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Subjects
Published
Boston : Addison-Wesley c2010.
Language
English
Main Author
Andrew Vickers, 1967- (-)
Physical Description
xii, 212 p. : ill. ; 24 cm
Bibliography
Includes bibliographical references (p. 209-210) and index.
ISBN
9780321629302
  • Introduction
  • How to Read this Book
  • 1. I tell a friend that my job is more fun than you'd think: What is statistics?
  • Describing Data
  • 2. So Bill Gates walks into a diner: On means and medians
  • 3. Bill Gates goes back to the diner: Standard deviation and interquartile range
  • 4. A skewed shot, a biased referee
  • 5. You can't have 2.6 children: On different types of data
  • 6. Why your high school math teacher was right: How to draw a graph
  • Data Distributions
  • 7. Chutes-and-ladders and serum hemoglobin levels: Thoughts on the normal distribution
  • 8. If the normal distribution is so normal, how come my dat'a never are?
  • 9. But I like that sweater: What amount of fit is a "good enough" fit?
  • Variation of Study Results: Confidence Intervals
  • 10. Long hair: A standard error of the older male
  • 11. How to avoid a rainy wedding: Variation and confidence intervals
  • 12. Statistical ties, and why you shouldn't wear one: More on confidence intervals
  • Hypothesis Testing
  • 13. Choosing a route to cycle home: What p-values do for us
  • 14. The probability of a dry toothbrush: What is a p-value anyway?
  • 15. Michael Jordan won't accept the null hypothesis: How to interpret high p-values
  • 16. The difference between sports and business: Thoughts on the t test and the Wilcoxon test
  • 17. Meeting up with friends: On sample size, precision and statistical power
  • Regression and Decision Making
  • 18. When to visit Chicago: About linear and logistic regression
  • 19. My assistant turns up for work with shorter hair: About regression and confounding
  • 20. I ignore my child's cough, my wife panics: About specificity and sensitivity
  • 21. Avoid the sales: Statistics to help make decisions
  • Some Common Statistical Errors, and What They Teach Us
  • 22. One better than Tommy John: Four statistical errors, some of which are totally trivial, but all of which matter a great deal
  • 23. Weed control for p-values: A single scientific question should be addressed by a single statistical test
  • 24. How to shoot a TV episode: Statistical analyses that don't provide meaningful numbers
  • 25. Sam, 93 years old, 700 pound Florida super-granddad: Two common errors in regression
  • 26. Regression to the Mike: A statistical explanation of why an eligible friend of mine is still single
  • 27. OJ Simpson, Sally Clark, George and me: About conditional probability
  • 28. Boy meets girl, girl rejects boy, boy starts multiple testing
  • 29. Some things that have never happened to me: Why you shouldn't compare p-values
  • 30. How to win the marathon: Avoiding errors when measuring things that happen over time
  • 31. The difference between bad statistics and a bacon sandwich: Are there "rules" in statistics?
  • 32. Look at your garbage bin: It may be the only thing you need to know about statistics
  • 33. Numbers that mean something: Linking math and science
  • 34. Statistics is about people, even if you can't see the tears
  • Discussion Section Answers
  • Credits and References
  • Index
Review by Choice Review

Understanding statistical concepts and accurately interpreting what computed results represent can be a major challenge for students and other users of data-driven investigations. This book masterfully provides 34 discussions regarding material encountered in an introductory course in a manner that is both entertaining and informative. Vickers (epidemiology and biostatistics, Memorial Sloan-Kettering Cancer Center) stresses conceptual underpinnings rather than computational technique. Generally three to five pages in length, the presentations balance careful explanations of the concept at hand, cautionary comments regarding common misconceptions, and illustrative examples that clarify related subtleties. Remarkably, the author does this in a way that is never heavy-handed. In fact, his use of lighthearted remarks, a blended mix of everyday examples and specialized but highly accessible settings from biostatistics, and effective cartoons make this book extremely readable. Each chapter ends with a summary box of "Things to Remember" and some discussion questions, which are fully answered in the back of the book. To put it simply, this work is a highly effective summary of basic statistical ideas, making it a valuable supplement to someone wanting to really grasp the interpretation of statistical results. Summing Up: Highly recommended. Lower-division undergraduates and general readers. N. W. Schillow Lehigh Carbon Community College

Copyright American Library Association, used with permission.