Recordings & Lecture Notes & Activities

Here are links to google drives that will contain all lecture notes and recordings (for both sections!) which will continue for as long as we’re asynchronous.

• Lecture Notes (just the pdf)
• Recordings (lecture notes included in the videos, with audio)

Activities

Once we move towards Unit 2, we’ll start to mix in some activities to our daily routine. Links to these will be updated throughout the semester.

• Monte Carlo (answer key)
• Metropolis Hastings (answer key)
• Gibbs Sampling (answer key)
• Intro to HMC in Stan (answer key)
  • gop.stan
  • laws.stan
• Hierarchical Models (answer key)
  • bayesian_slr_completepooling.stan
  • bayesian_slr_partialpooling.stan

Assorted Extra Notes

• A note on numerical instability in Metropolis-Hastings acceptance probabilities

  • R code example

• Model Statements -> Stan code (examples)

  • Normal-Normal

  • Bayesian Simple Linear Regression

• TR1: Making the data “moot” by having the prior agree with it

• The issue with returning 0 in the unnormalized posterior plausability function

• Bayesian SLR, full conditional derivations (PS2 Q5)