The best books for learning about open science and how to do better research with better statistics

The Books I Picked & Why

The Seven Deadly Sins of Psychology: A Manifesto for Reforming the Culture of Scientific Practice

By Chris Chambers

Book cover of The Seven Deadly Sins of Psychology: A Manifesto for Reforming the Culture of Scientific Practice

Why this book?

Still the best book to diagnose the problems and explain why we need Open Science. Chris Chambers tells of his disillusionment with so many aspects of what researchers were doing, in psychology, but also in medicine and many other fields. That rang true to me—I travelled that same road. He goes on from explaining the problems to describing solutions. Many of these, including openness, better statistics, replication, and increased scrutiny, are now being advocated or required by funders and journal editors, and adopted by researchers. That’s Open Science, hooray!


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Science Fictions: How Fraud, Bias, Negligence, and Hype Undermine the Search for Truth

By Stuart Ritchie

Book cover of Science Fictions: How Fraud, Bias, Negligence, and Hype Undermine the Search for Truth

Why this book?

I love how Ritchie starts with a rather wry account, addressed directly to you as a would-be researcher, of the challenges and weirdness you’ll encounter as you launch into your own research. His own research helped sparked recognition of the ‘replication crisis,’ so he’s well placed to tell us about misguided practices and the sometimes wicked deeds of researchers. More happily, he describes how we can return to the sound foundations of good scientific practice. A current term for that is ‘Open Science.’


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Beyond Significance Testing

By Rex B. Kline

Book cover of Beyond Significance Testing

Why this book?

You may have heard of ‘significance testing,’ and the magical ‘p < .05,’ which somehow makes a research result ‘significant,’ which is often taken as (almost) ‘true.’ Even if you haven’t heard of all that, Kline explains clearly why significance testing has been disastrous for science, leading to misleading conclusions and much valuable research not even being reported. He draws on my work to explain how ‘the new statistics’ (estimation) is a much better way to understand results. The first chapter is fairly easy reading. Later chapters are also terrific but get more technical as Kline explains lots of ways to do things better. As I’m quoted on the back cover “Read this book and see the future!” Happily, the future is increasingly looking as Kline recommended.


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Research Methods in Psychology: Evaluating a World of Information

By Beth Morling

Book cover of Research Methods in Psychology: Evaluating a World of Information

Why this book?

Yes, this is a textbook but, if you are seeking a research design and methods text for psychology or a related discipline, this is easily my top choice. There are lots of references to topical stories to keep everything relevant for students. There’s a truckload of valuable stuff online to support both teachers and learners. This fourth edition is right up-to-the-moment, Chapter 3 especially so, as it explains three types of scientific claims, and four types of validity that researchers should aim to achieve. That may sound forbidding, but Morling’s examples and explanations are pleasingly accessible.  


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The Design of Experiments in Neuroscience

By Mary E. Harrington

Book cover of The Design of Experiments in Neuroscience

Why this book?

Another research design textbook, this one more specifically about neuroscience. My co-author, neuroscientist Robert Calin-Jageman, highly recommends it. This third edition has clear and up-to-date discussions of issues such as p hacking and publication bias that emphasise the need for Open Science. There’s a focus on effect sizes and confidence intervals, as in the new statistics. The book also describes strategies needed to enhance the rigor and reproducibility of neuroscience research.


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