Chapter 4 STAT 207: Intermediate Bayesian Statistical Modeling

This chapter contains past exam problems of STAT 207: Intermediate Bayesian Statistical Modeling. The textbook used for this class is Gelman et al. (2014). Belowing is the syllabus of this class for First Year Exam (2020).

• Single and multi-parameter models.

• Normal approximations to the posterior distribution.

• Bayesian inference for hierarchical models.

• Model comparison and model assessment.

• Modeling accounting for data collection.

• Posterior simulation.

• Approximations to the posterior distribution based on posterior modes.

• Bayesian inference for regression models and hierarchical linear models.

• Models for robust inference.

• Mixture models.

References

Gelman, Andrew, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin. 2014. Bayesian Data Analysis. 3rd ed. Boca Raton, FL: Chapman; Hall.