0. 课程概述
1. 初识贝叶斯法则(Bayes'Rule)
2. 一个真正的贝叶斯模型——Beta-Binomial Model
3. Balance and Sequentiality in Bayesian Analyses
4. Bayesian Inference:From Traditional Foundations to Current Practices
5. Markov Chain Monte Carlo(MCMC)
6. Posterior Inference & Estimation
7. A Simple Linear Regression Model with PyMC
8. Bayes Factor
9. Multivariable linear regression
10. Evaluating Regression Models
11. Logistic Regression
12. Hierarchical Models
13. Hierarchical Regression Models
14. 课程回顾与复习
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