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

4.4 out of 5 stars 50 customer reviews
ISBN-13: 978-0321629302
ISBN-10: 0321629302
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Editorial Reviews

From the Back Cover

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.
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Product Details

  • Paperback: 240 pages
  • Publisher: Pearson; 1 edition (November 28, 2009)
  • Language: English
  • ISBN-10: 0321629302
  • ISBN-13: 978-0321629302
  • Product Dimensions: 6.9 x 0.5 x 9.2 inches
  • Shipping Weight: 10.4 ounces (View shipping rates and policies)
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (50 customer reviews)
  • Amazon Best Sellers Rank: #22,912 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

By Jane L. Harvill on July 16, 2010
Format: Paperback
I'm a Ph.D. statistician at Baylor University in the Department of Statistical Science. I teach statistics courses at many different levels, and read several statistics books a year. I'm always on the lookout for a good book that my students can relate to, but rarely - if ever - have I found a book I can recommend to my colleagues, our department's Ph.D. students, M.S. students, undergraduate majors, and those students who are majoring in some other subject area (not statistics) who are required to take a statistics course. That was, until now ...

The little monograph by Andrew Vickers is absolutely a fun book to read - and how many times can it be said that a book about P-values is fun? My husband is often subjected to my very serious face and quietness as I read a statistics book. He often jokes that I look like I'm angry or in pain. But with this book, heard me laugh out loud, and do so often. Andrew Vicker's "What is a p-Value Anyway?" contains 34 short stories that wittily illustrate the correct way to think about and apply statistics in terms everyone can relate to and understand.

Vickers manages to put statistical concepts into a fun, understandable light that is entertaining and informative, no matter what your level of understanding and education in statistics. I highly recommend this book.
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Format: Paperback
A couple of years ago, because on an error (?) in the IT system of the Italian IRS (Tax Agency), the incomes of all Italians were downloadable from the Agency site. The "error" was discovered and cleared after a few hours, but in the meantime a lot of people had already downloaded the files.
So did a friend of mine, living in Milan. Early in the morning he called me. His voice sounded, at the same time, angry and depressed. "How can I be so underpaid? I downloaded the incomes of people living in Milan and computed and re-computed the average all the night. I discovered that my salary is very, very low! The mean income of people in Milan is much higher!!" "Well, that's the Berlusconi's effect", I replied, "don't worry, take the median instead of the mean, and you'll recover your self-esteem... and stop your wife's complains".
But I wasn't persuasive enough...at the phone, without paper and pencil, I couldn't explain him the impact of outliers and the meaning of skewness, and he started looking for another job.
Had this happened now, I would simply send him a copy of "What is a p-value anyway", and a couple of pages at the beginning would explain him the concepts, using Bill Gates instead of Berlusconi. The concepts and ideas of statistics are indeed the focus of this book, from basic ones like median and mean, to more advanced ones like hypothesis testing, regression, logistic regression, survival analysis etc. These concepts are explained, without formulas, by means of funny stories, that you can tell to your friends at a party, or use with your students to raise their attention. Moreover, stories stay attached to our neurons, and we, or our student, don't forget them and their embedded concepts.
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Format: Paperback Verified Purchase
I bought this book thinking that it might provide good simple explanations of statistics, in particular to help colleagues and students. The author writes well and provides some good, amusing examples (like Bill Gates walks into a bar, and the average salary is $100 million). But, I cannot recommend the book, because it will train people to use “p-values”. The author LOVES p-values. He likes p-values like fried food. He knows they are bad for you, but he keeps using them; it’s like a nutrition book where every chapter has a deep-fried recipe. I should have seen this coming from the title, but the previous reviews sounded so good.

Since then I’ve found Geoff Cumming’s book (Understanding the New Statistics). Spend the extra bucks and get it. He’s entertaining (great visuals) and will really teach you what you need to know about doing sound statistics, and no p-values.

If you care to bear with me, let’s talk about p-values.

If you’ve taken an intro stats course you were taught to do your stat, state a “null hypothesis” that your result is caused by chance, then find the p-value (computed by the software) to see if it was caused by “chance”. If p is > 0.05 (or 0.01) your result is “statistically not-significant”, and you lose. If the p-value is <0.05 your result is “statistically significant” and you win. Vickers knows this is a big problem. In chapter 13, he explains how null hypothesis testing (p-values) doesn’t really tell you what you want to know. (A “null hypothesis” is that there is no difference or nothing happened.) In chapter 14, he waffles on about it. In chapter 15, he shows how a LARGE p (>0.05) doesn’t actually tell you that your result is “insignificant”.
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Format: Paperback
This book aims to provide a primarily qualitative understanding of key ideas in statistics. The approach is to describe the ideas in some detail, illustrated with examples, while almost entirely avoiding math. Overall, I think the author has made a good effort in this regard, and his humor does liven things up, but ultimately the strict avoidance of the math proves to be a significant limitation. Every mathematical formula may not be worth a thousand words, but the good ones come close. I can still recommend this book, but I think that a book which doesn't shy away from presenting at least some math would be a better choice for most people.

In any case, here are the key ideas from the book which I found noteworthy:

(1) As measures of central tendency, both mean and median values have their use. Medians are often more useful when there are outliers, whereas means are often more useful for decision-making. Using both together will sometimes also make sense.

(2) Normal distributions describe many natural phenomena, as well as the additive effect of many random events (central limit theorem). However, many phenomena are limited to non-negative values and involve multiplicative effects, so the resulting distributions are non-normal and right-skewed; sometimes these distributions can be converted to normal by taking the log of the data.

(3) With normal distributions, about 50% of data falls within 2/3 of a standard deviation, 67% within one standard deviation, and 95% within two standard deviations (the typical confidence interval). When data are highly skewed, medians and percentiles (eg, quartiles) are often more useful than means and standard deviations.

(4) Study bias can come from many sources during study design, conduct, and analysis.
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