I teach Bayesian statistics in R and psychophysiology at the University of Sussex. I also offer workshops to external universities (see here for details)

• GitHub Workshop (MRes - 12/25)

• Cognitive Neuroscience (Undergrad)
  • The Embodied Brain
• Topics in Neuroscience (CogNeuro MSc)
  • Interoception

• Intro to Bayesian Statistics (University of Paris-Cité - 12/24)

• Lecture 1:
  • RefreshR: R basics
  • Distributions: The Normal distribution
• Lecture 2:
  • Distributions: Other distributions
  • Frequentist Framework: Until slide 13
• Lecture 3:
  • Frequentist Framework
  • Bootstrapping: Until slide 34
• Lecture 4:
  • Bootstrapping
  • Bayesian Theorem: Until slide 28
• Lecture 5:
  • Bayesian Theorem
  • Bayes Factors (BIC approximation)
• Lecture 6:
  • Bayes Factors
• Lecture 7:
  • Posteriors
  • Module evaluation
• Lecture 8:
  • brms - Priors
• Lecture 9:
  • brms - Posteriors
• Lecture 10:
  • Model Comparison
  • might or might not be a rickroll

• Cognitive Neuroscience (Undergrad)
  • The Embodied Brain
• Topics in Neuroscience (CogNeuro MSc)
  • Interoception

• Physiology (University of Basel - 04/24)
  • Slides
  • Experiment

• Lecture 1
• Lecture 2
• Lecture 3
• Lecture 4
• Lecture 5 & 6
• Lecture 7
• Lecture 8 & 9
• Lecture 10
• Lecture 11