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Index
Statistics Done Wrong: The Woefully Complete Guide
About the Author
Preface
Acknowledgments
Introduction
1. An Introduction to Statistical Significance
The Power of p Values
Psychic Statistics
Neyman-Pearson Testing
Have Confidence in Intervals
2. Statistical Power and Underpowered Statistics
The Power Curve
The Perils of Being Underpowered
Wherefore Poor Power?
Wrong Turns on Red
Confidence Intervals and Empowerment
Truth Inflation
Little Extremes
3. Pseudoreplication: Choose Your Data Wisely
Pseudoreplication in Action
Accounting for Pseudoreplication
Batch Biology
Synchronized Pseudoreplication
4. The P Value and the Base Rate Fallacy
The Base Rate Fallacy
A Quick Quiz
The Base Rate Fallacy in Medical Testing
How to Lie with Smoking Statistics
Taking Up Arms Against the Base Rate Fallacy
If At First You Don’t Succeed, Try, Try Again
Red Herrings in Brain Imaging
Controlling the False Discovery Rate
5. Bad Judges of Significance
Insignificant Differences in Significance
Ogling for Significance
6. Double-Dipping in the Data
Circular Analysis
Regression to the Mean
Stopping Rules
7. Continuity Errors
Needless Dichotomization
Statistical Brownout
Confounded Confounding
8. Model Abuse
Fitting Data to Watermelons
Correlation and Causation
Simpson’s Paradox
9. Researcher Freedom: Good Vibrations?
A Little Freedom Is a Dangerous Thing
Avoiding Bias
10. Everybody Makes Mistakes
Irreproducible Genetics
Making Reproducibility Easy
Experiment, Rinse, Repeat
11. Hiding the Data
Captive Data
Obstacles to Sharing
Data Decay
Just Leave Out the Details
Known Unknowns
Outcome Reporting Bias
Science in a Filing Cabinet
Unpublished Clinical Trials
Spotting Reporting Bias
Forced Disclosure
12. What Can Be Done?
Statistical Education
Scientific Publishing
Your Job
A. Notes
Introduction
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
B. Colophon
C. Updates
Index
Copyright
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