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Up to date introductions to psychology, stats, and genomics -- 2019 March

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Up to date introductions to psychology, stats, and genomics -- 2019 March

Emil O. W. Kirkegaard
Mar 27, 2019
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Up to date introductions to psychology, stats, and genomics -- 2019 March

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A fellow emailed me asking for help on what to start reading to learn psychology and stats. The replication crisis means that most older psychology introductions should be viewed with distrust, and the various new streams in stats means that much of the stuff in stats textbooks, while not wrong, is less than optimal. In the optimal world, there would be a new textbook on various psychology topics that covered all the important ideas that failed replication (stereotype threat, growth mindset etc.),  and especially the things that did not fail (stereotype accuracy, IQ testing, behavioral genetics [not candidate or GxE]). Unfortunately, this doesn't exist yet. However, the below are a reasonable start in my opinion.

Psychology:

  • Chambers, C. (2017). The seven deadly sins of psychology: A manifesto for reforming the culture of scientific practice. Princeton University Press.

  • Buss, D. (2019). Evolutionary psychology: The new science of the mind. Psychology Press. 6th edition

    • I believe evolutionary psychology is generally sound and on good theoretically footing, but beware specific claims about hormone cycles, which I think are doubtful.

  • Ritchie, S. (2015). Intelligence: All that matters. Hodder & Stoughton. Review

    • This good is quite good, but beware the author hates group differences, and this book does not cover that important research.

  • Knopik, V. S., Plomin, R., DeFries, J. C., & McClearn, G. E. (2016). Behavioral genetics. Macmillan. 7th edition

    • This book mostly covers main findings, not details of methods.

I'm open to recommendations that cover more subfields, but I'm not aware of any post-crisis introduction to e.g. social psychology.

Stats:

  • Cumming, G. (2013). Understanding the new statistics: Effect sizes, confidence intervals, and meta-analysis. Routledge.

  • James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning. New York: Springer. Free

    • Unorthodox choice, but the best stats book I've read.

Bonus, for genomics I recommend:

  • Reich, D. (2018). Who we are and how we got here: Ancient DNA and the new science of the human past. Oxford University Press.

  • Archibald, J. M. (2018). Genomics: A Very Short Introduction. Oxford University Press.

  • Snyder, M. (2016). Genomics and personalized medicine: what everyone needs to know. Oxford University Press.

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