Tag Archives: cognitive science

Michael Lee

In this episode JP and Alex interview Michael Lee. They discuss model complexity and generative models, the differences between cognitive models and machine learning, whether and when preregistration of models is useful, and Michael’s undying love of cricket.

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Notes and links:

  • Follow Michael on twitter: https://twitter.com/mdlBayes
  • The workshop we attended resulted in this special issue on robust modeling in cognitive science: https://link.springer.com/journal/42113/volumes-and-issues/2-3
  • Lee and Vanpaemel on informative priors: https://link.springer.com/article/10.3758/s13423-017-1238-3

Zoltan Dienes

In this episode JP and Alex interview Zoltan Dienes. They discuss Zoltan's passion for the martial arts, 
why Bayesian inference could be more Popperian than you might think, 
and the easiest way to start using Bayesian statistics in practice.

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Notes and links:

- Zoltan’s book: https://www.amazon.com/Understanding-Psychology-Science-Introduction-Statistical/dp/023054231X
- Zoltan’s Bayes references and Bayes factor calculator: http://www.lifesci.sussex.ac.uk/home/Zoltan_Dienes/inference/Bayes.htm
- Four reasons to prefer Bayesian over significance testing: https://link.springer.com/article/10.3758/s13423-017-1266-z

JP and Alex 2.0

In this episode JP and Alex catch up with each other and talk about how they like podcasting so far, Alex’s experience doing a joint MS/Phd in stats and cognitive science, JP’s new paper responding to the p<.005 debate, and their future plans for the podcast.

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Notes and links:

  • JP’s entry into the .005 debate: https://link.springer.com/article/10.3758/s13423-018-1523-9 (preprint: https://psyarxiv.com/rbm8y)
  • Notes on Kullback-Leibler divergence: https://psyarxiv.com/5vhzu/