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What Is A P-Value Anyway?

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Table of Contents

Introduction 0. 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 data 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 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. A statistical theory of how to get a five-year old boy to brush his teeth: defining the p-value 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 that are totally trivial, but 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: avoiding 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 girls, 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

About the Author

Andrew Vickers, PhD, is an Associate Attending Research Methodologist in the Department of Epidemiology and Biostatistics at Memorial Sloan-Kettering Cancer Center in New York. He is active in a variety of fields of cancer research, and also conducts original research in statistical methods, particularly with respect to the evaluation of prediction models. Dr. Vickers has been course leader for the biostatistics course at the Memorial Sloan-Kettering Cancer Center since 2001, and has taught biostatistics to medical students at Cornell Medical School since 2000. Dr. Vickers received a First Class BA in History and Philosophy of Science from the University of Cambridge and a PhD in Clinical Medicine from the University of Oxford.

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