Rent 9780321629302 | What Is a P-Value Anyway? : 34 Stories to Help You Actually Understand Statistics

Summary Table of Contents Author Biography

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.What is a p-value Anyway? is the perfect compliment to any introductory statistics textbook and will succeed in demonstrating the everyday importance of statistics to your class.

Introduction
How to Read this Book	p. ix
I tell a friend that my job is more fun than you'd think: What is statistics?	p. 1
Describing Data
So Bill Gates walks into a diner: On means and medians	p. 4
Bill Gates goes back to the diner: Standard deviation and interquartile range	p. 7
A skewed shot, a biased referee	p. 12
You can't have 2.6 children: On diffe... MORErent types of data	p. 16
Why your high school math teacher was right: How to draw a graph	p. 21
Data Distributions
Chutes-and-ladders and serum hemoglobin levels: Thoughts on the normal distribution	p. 26
If the normal distribution is so normal, how come my dat'a never are?	p. 32
But I like that sweater: What amount of fit is a "good enough" fit?	p. 37
Variation of Study Results: Confidence Intervals
Long hair: A standard error of the older male	p. 41
How to avoid a rainy wedding: Variation and confidence intervals	p. 46
Statistical ties, and why you shouldn't wear one: More on confidence intervals	p. 50
Hypothesis Testing
Choosing a route to cycle home: What p-values do for us	p. 54
The probability of a dry toothbrush: What is a p-value anyway?	p. 57
Michael Jordan won't accept the null hypothesis: How to interpret high p-values	p. 61
The difference between sports and business: Thoughts on the t test and the Wilcoxon test	p. 64
Meeting up with friends: On sample size, precision and statistical power	p. 70
Regression and Decision Making
When to visit Chicago: About linear and logistic regression	p. 77
My assistant turns up for work with shorter hair: About regression and confounding	p. 84
I ignore my child's cough, my wife panics: About specificity and sensitivity	p. 90
Avoid the sales: Statistics to help make decisions	p. 95
Some Common Statistical Errors, and What They Teach Us
One better than Tommy John: Four statistical errors, some of which are totally trivial, but all of which matter a great deal	p. 99
Weed control for p-values: A single scientific question should be addressed by a single statistical test	p. 102
How to shoot a TV episode: Statistical analyses that don't provide meaningful numbers	p. 105
Sam, 93 years old, 700 pound Florida super-granddad: Two common errors in regression	p. 110
Regression to the Mike: A statistical explanation of why an eligible friend of mine is still single	p. 116
OJ Simpson, Sally Clark, George and me: About conditional probability	p. 119
Boy meets girl, girl rejects boy, boy starts multiple testing	p. 124
Some things that have never happened to me: Why you shouldn't compare p-values	p. 130
How to win the marathon: Avoiding errors when measuring things that happen over time	p. 133
The difference between bad statistics and a bacon sandwich: Are there "rules" in statistics?	p. 139
Look at your garbage bin: It may be the only thing you need to know about statistics	p. 142
Numbers that mean something: Linking math and science	p. 147
Statistics is about people, even if you can't see the tears	p. 151
Discussion Section Answers	p. 154
Credits and References	p. 209
Index	p. 211
Table of Contents provided by Ingram. All Rights Reserved.

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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