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What Is a P-value Anyway? (10 Edition)by Andrew Vickers
Synopses & ReviewsPlease note that used books may not include additional media (study guides, CDs, DVDs, solutions manuals, etc.) as described in the publisher comments.
Focusing on everyday applications as well as those of scientific research, this classic of modern statistical methods requires little to no mathematical background. Readers develop basic skills for evaluating and using statistical data. Lively, relevant examples include applications to business, government, social and physical sciences, genetics, medicine, and public health.
"W. Allen Wallis and Harry V. Roberts have made statistics fascinating." — The New York Times
"The authors have set out with considerable success, to write a text which would be of interest and value to the student who, not concerned primarily with statistical technics, must understand the nature and methodology of the subject in order to make proper use of its results." — American Journal of Public Health and the Nation's Health
"This book is a distinct and important contribution to the text literature in statistics for social scientists and should be given careful consideration by sociologists." — American Sociological Review.
Classic text focuses on everyday applications as well as those of scientific research. Minimal mathematical background necessary. Includes lively examples from business, government, and other fields. "Fascinating." — The New York Times. 1962 edition.
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.
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
For all readers interested in statistics.
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.
Table of Contents
0. How to read this book
1. I tell a friend that my job is more fun than you'd think: What is statistics?
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
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
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
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