Statistics Done Wrong: The Woefully Complete Guide

Detailed Summary of the Book

At its heart, Statistics Done Wrong is a no-nonsense guide dedicated to exposing the most common and consequential errors that plague modern statistics. The book is divided into several key areas that cover a wide range of statistical pitfalls and misconceptions. Whether you're a biology researcher grappling with p-values, a psychologist navigating hypothesis testing, or a data analyst trying to avoid confirmation bias, this book provides practical advice in a way that's both accessible and engaging.

The book walks readers through concepts such as statistical power, effect sizes, multiple comparisons, and reproducibility in science. Beyond the theory, it provides tangible examples of how these concepts are misused and misunderstood in real-life studies. By shedding light on these problems, the book doesn't just tell you what not to do—it empowers you to conduct better, more reliable research.

You'll also find that this is not a dry statistics textbook. The writing is approachable, peppered with humor, and filled with lessons that stick with you long after you've put it down. Whether you're a beginner or someone with statistical experience, you'll gain new insights into how statistics should be used—and how they should never be abused.

Key Takeaways

• Understand the dangers of relying solely on p-values and learn about alternative metrics, such as effect sizes and confidence intervals.
• Discover why statistical power matters and how an underpowered study can lead to misleading conclusions.
• Learn about the problem of multiple comparisons and the false positives they create if not properly accounted for.
• Gain insight into reproducibility crises in scientific research and how to avoid contributing to them.
• Develop a critical mindset toward statistical claims made in scholarly articles, news stories, and everyday data interpretations.

Famous Quotes from the Book

"The p-value isn’t magic. It won’t save you from flawed experiment design, selection bias, or wishful thinking."

"Statistical power isn’t an obscure technical detail—it’s the beating heart of why scientific studies work. Or, more often, why they fail."

"If you tortured your data until it confessed, you shouldn’t be surprised when it tells a lie."

Why This Book Matters

Statistics is a powerful tool for understanding the world, but it’s also a double-edged sword. Poorly executed or misunderstood statistics can lead to faulty conclusions that ripple through academic fields, public policy, and even individual behavior. This book shines a spotlight on these issues, empowering readers with the skills necessary to question and refine their use of data.

With the rise of big data and the increasing influence of algorithms on our lives, the need for statistical literacy has never been more urgent. Statistics Done Wrong matters because it fills a critical gap in education, providing a guide that goes beyond formulas and dives into real-world issues. By addressing how statistics are misapplied, the book advocates for a culture of rigor, transparency, and ethics within research communities and beyond.

In short, this book is for anyone who cares about getting statistics right, whether you're conducting research yourself or simply trying to understand the numbers and headlines that surround you in daily life.