[Part 1.] Introduction -- 1. I tell a friend that my job is more fun that you'd think: what is statistics? -- [Part 2.] 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 -- [Part 3.] 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? -- [Part 4.] 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 -- [Part 5.] 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 -- [Part 6.] 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 -- [Part 7.] 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

Presents the essential concepts in thirty-four brief stories. Drawing on his experience as a medical researcher, Vickers blends explanations and humor with minimal math, to help readers understand and interpret the statistics they read every day. --from publisher description