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What is a p-value anyway? 34 Stories to Help You Actually Understand Statistics, 1st edition

  • Andrew J. Vickers

Published by Pearson (November 18th 2009) - Copyright © 2010

1st edition

Overview

KEY BENEFIT: What is a p-value Anyway? offers a fun introduction to the fundamental principles of statistics, presenting the essential concepts in thirty-four brief, enjoyable stories. Drawing on his experience as a medical researcher, Vickers blends insightful explanations and humor, with minimal math, to help readers understand and interpret the statistics they read every day.

 

KEY TOPICS: Describing data; Data distributions; Variation of study results: confidence intervals; Hypothesis testing; Regression and decision making; Some common statistical errors, and what they teach us

 

MARKET: For all readers interested in statistics.

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

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