These course materials were developed under NSF awards DEB-1145200, DBI-1052875 and DBI-163914.

- Participant and Course Introduction
- What Sets Bayes Apart?
- Differences among the three branches of statistics illustrated with confidence envelopes
- Rules of Probability & Probability Lab 1
- Probability Concepts and Notation
- Probability Distributions & Probability Lab 2
- Probability Distributions Boardwork
- Distributional Cheatsheet
- Welcome Happy Hour at SESYNC!

Review Hobbs and Hooten chapters 1-3.

- Marginal Distributions & Probability Lab 3
- Moment Matching & Probability Lab 4
- Likelihood & Lab
- Likelihood Lab Excel File & Answer

Review Hobbs and Hooten chapters 3.5-4.

- Likelihood Lab Continued
- Bayes’ Theorem & Lab
- More about Priors I & Lab
- Beta-binomial Conjugacy Derivation

Review Hobbs and Hooten chapters 5 and 7.

- MCMC Gibbs Sampling & MCMC Lab 1
- MCMC Gibbs Sampling Math
- JAGS Primer & Lab Answers
- MCMC Metropolis-Hastings (optional) & MCMC Lab 2 (optional)

Review Hobbs and Hooten chapter 7-8.

- JAGS Primer Continued & Lab Answers
- JAGS Problems Lab
- Inference From a Single Model
- Bayesian Regression
- Lognormal Explanation

Review Hobbs and Hooten chapter 6.

Review Hobbs and Hooten chapters 6, 10-12.

Review Hobbs and Hooten chapters 6, 8, 10-12.

- Writing Hierarchical Models Lab Continued
- More About Priors II
- Mixture Models, Zero Inflation & Occupancy & Lab

- Course Evaluation Survey
- Dynamic Models & Lynx Lab
- Spatial Modeling for Continuous Data & Spatial Lab
- Spatial Modeling for Areal Data (optional)
- Farewell Happy Hour at SESYNC!