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Statistics Done Wrong
152 pages
A pithy, eye-opening guide that transforms the dread of statistical errors into empowering methodological clarity.
What it feels like
Reading this book feels like sitting down with a sharp, no-nonsense mentor who is determined to save you from embarrassing professional blunders. The pace is brisk and the prose is deliberately pithy, cutting through the dense fog of scientific politics and complex methodology with refreshing directness. It cultivates a mood that is both cautionary and deeply clarifying, exposing the widespread misconceptions that plague modern research before offering a pragmatic path forward. Rather than drowning the reader in dry equations, it focuses on the experiential themes of scientific integrity and methodological rigor. It is an essential, empowering read for scientists, statisticians, and researchers who want to bulletproof their work and champion a higher standard of analytical truth.
- Mood
- intellectually stimulating
- cautionary
- clarifying
- Tone
- wry
- instructive
- direct
- critical
- pragmatic
- Pace
- brisk
- Themes
- scientific integrity · methodological rigor · the pitfalls of research · correcting misconceptions
- The writing
- Concise, pithy, and direct, cutting through complex mathematical concepts with pragmatic clarity.
- The arc
- Moves from the shock of widespread scientific errors to the empowering clarity of doing things right.
- Who it's for
- Scientists, researchers, and data enthusiasts who want to bulletproof their methodology and avoid embarrassing analytical blunders.
About the book
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.
Description from Open Library.
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