Free online courseBayesian Statistics Lecture

Course content

• Video class: [Introduction] Course orientation

  0h34m

• Video class: [Introduction] Interpretation of probability and Bayes' rule part 1

  0h27m

• Video class: [Introduction] Interpretation of probability and Bayes' rule part 2

  0h25m

• Video class: [Introduction] Bayesian inference

  0h31m

• Video class: [Introduction] Probability review part 1

  0h10m

• Video class: [Introduction] Probability review part 2

  0h40m

• Video class: [Bayesian inference for a proportion] Example and discrete priors part 1

  0h10m

• Video class: [Bayesian inference for a proportion] Discrete priors part 2

  0h36m

• Video class: [Bayesian inference for a proportion] Continuous prior: the Beta distribution

  0h24m

• Video class: [Bayesian inference for a proportion] Updating the beta prior

  0h44m

• Video class: Lab 1

  0h10m

• Video class: [Bayesian inference for a proportion] Bayesian inference with continuous priors

  0h48m

• Video class: [Bayesian inference for a mean] Example

  0h14m

• Video class: [Bayesian inference for a mean] Prior and posterior for mean and standard deviation part 1

  0h09m

• Video class: [Bayesian inference for a mean] Prior and posterior for mean and standard deviation part 2

  0h55m

• Video class: [Bayesian inference for a mean] Prior and posterior for mean and standard deviation part 3

  0h29m

• Video class: Lab 2

  0h04m

• Video class: [Bayesian inference for a mean] Gamma-Poisson conjugacy exercise

  0h11m

• Video class: [Bayesian inference for a mean] Monte Carlo approximation

  0h16m

• Video class: [Gibbs sampler and MCMC] Example and prior and posterior derivations for mean and standard deviation

  1h04m