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Statistics Done Wrong

Statistics Done Wrong
作者:Alex Reinhart
副标题:The Woefully Complete Guide
出版社:No Starch Press
出版年:2015-03
ISBN:9781593276201
行业:其它
浏览数:126

内容简介

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong.

Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics.

You'll find advice on:

Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan

How to think about p values, significance, insignificance, confidence intervals, and regression

Choosing the right sample size and avoiding false positives

Reporting your analysis and publishing your data and source code

Procedures to follow, precautions to take, and analytical software that can help

Scientists: Read this concise, powerful guide to help you produce statistically sound research.

Statisticians: Give this book to everyone you know.

The first step toward statistics done right is Statistics Done Wrong.

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作者简介

Alex Reinhart is a statistics instructor and PhD student at Carnegie Mellon University. He received his BS in physics at the University of Texas at Austin and does research on locating radioactive devices using statistics and physics.

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目录

Introduction

Chapter 1: An Introduction to Statistical Significance

Chapter 2: Statistical Power and Underpowered Statistics

Chapter 3: Pseudoreplication: Choose Your Data Wisely

Chapter 4: The p Value and the Base Rate Fallacy

Chapter 5: Bad Judges of Significance

Chapter 6: Double-Dipping in the Data

Chapter 7: Continuity Errors

Chapter 8: Model Abuse

Chapter 9: Researcher Freedom:Good Vibrations?

Chapter 10: Everybody Makes Mistakes

Chapter 11: Hiding the Data

Chapter 12: What Can Be Done?

Notes

Index

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读书文摘

译者注:p值就是当原假设为真时,比所得到的样本观察结果更极端的结果出现的概率。

通常来说,我们观测的是由于巧合或随机变化导致的差异,所以当观测差异大于随机产生的差异时,统计学家称之为“统计意义上的显著区别”

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