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A Demon Army in Santiago: Explaining Bayesian Model-Averaging With a Cartoon

Last week I attended the 84th Annual Meeting of the Psychometric Society in Santiago, Chili. Together with Maarten Marsman I taught a JASP workshop on Monday, and then gave a keynote on Tuesday. The keynote was called “Bayesian multi-model inference for practical and impractical problems” and you can find the slides here. Due to poor planning on my side, I could only present the practical problems, not the impractical ones.

If Your First Baby is Early, Will Your Second Baby be Early?

This post was written the week before the birth of our daughter Leanne, who finally decided to make an appearance on Valentine’s Day this year.

Nataschja is lying on our sofa, watching a series on Netflix. It is Tuesday afternoon and I am working from home. In fact, I have been working from home for about a week now, awaiting the birth of our daughter. Both Nataschja and I are getting impatient, and the uncertainty surrounding the timing of the birth isn’t helping. Non-medical labor can start anywhere from week 37 to week 42, and that is a pretty wide time window.

An Inconvenient Truth

On June 6th I gave a one-hour lecture for SIOS, the Student Initiative for Open Science in Amsterdam (you can follow them on Twitter @StudentIOS). The slides are at https://osf.io/5s9uq/, and a YouTube video of the entire lecture is at https://t.co/u7bkqaC6Ko.



This presentation consists of three parts. In the first, I will present a whirlwind tour of the p-value’s many statistical peculiarities. In the second, I will list reasons for the p-value’s continued dominance across the empirical sciences. One such reason is that the p-value can be used to silence your skeptics — that is, to discredit the null hypothesis that the experimental treatment was utterly ineffective. In the third part I will demonstrate how Bayesian hypothesis testing with JASP (jasp-stats.org) can provide a practical, principled, and easy-to-use alternative.

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