21 August 2021
Bayesian Statisticsonline course
Bayesian data analysis is a rapidly developing field of statistics, which has many useful applications in various areas of political science, sociology, and international relations. The goal of this course is to provide a brief and “mostly harmless” (that is, as informal as possible) introduction to the theory and application of Bayesian statistical methods. The course begins with the basic concepts of Bayesian statistics (e.g., conditional probability, Bayes’ theorem, prior and posterior distribution). Then we consider various approaches to the estimation and assessment of Bayesian models (with the focus on MCMC methods) in the context of generalized linear models. Next we learn about main Bayesian approaches to model selection, including Bayes factors, DIC, and cross-validation methods. We conclude by discussing Bayesian model averaging (BMA), a powerful Bayesian approach to reducing model specification uncertainty.
Students are assumed to have basic knowledge of statistics and be familiar with several conventional statistical methods, most importantly regression analysis. Knowledge of advanced topics, such as multilevel regression analysis and maximum-likelihood estimation, is helpful, but not critical. In addition, for practical exercises we will use R programming environment, so another major prerequisite is basic knowledge of R.
Boris Sokolov, Senior Research Fellow at Ronald F. Inglehart Laboratory for Comparative Social Research; Associate Professor at the Department of Sociology (HSE St. Petersburg)
Participation in the IPSA - HSE Summer School is open to students of all levels of study, academics and professionals, provided they meet the prerequisites specified for courses.
Day 1: The fundamentals of Bayesian statistics. R packages for Bayesian modeling. Bayesian GLMs.
Day 2: Bayesian model estimation. Markov chain Monte Carlo methods. Key convergence diagnostics.
Day 3: Bayesian model evaluation. Posterior predictive checks.
Day 4: Bayesian model comparison and model averaging
Day 5: Preparation and presentation of research projects
ECTS are given upon successful completion of examination procedures.
EUR 175: General fee. All fees will have to be paid in rubles. EUR 175 ≈ RUB 15900
All applicants are to pay the non-refundable registration fee of EUR 10 ≈ RUB 900.
EUR 120: The discounted fee that can be paid by:
- Students and employees of Russian universities and research (education) institutions, including HSE University and its campuses;
- IPSA Methods Schools alumni, including the alumni of the IPSA-HSE Summer School;
- Citizens of the developing countries, according to the following list: https://spb.hse.ru/mirror/pubs/share/242571054
EUR 120 ≈ RUB 10900