In 2015, the ICPSR Summer Program is offering four workshops on Bayesian analysis.

**Three- to Five-Day Workshops**

July 7-10, 2015

Doing Bayesian Data Analysis: An Introduction

**LOCATION:**Ann Arbor, MI

**INSTRUCTOR:**John Kruschke, Indiana University

**DESCRIPTION:**This workshop introduces participants to modern Bayesian methods. We will begin with the basic ideas of probability and Bayes' rule. After that, we move on to cover probability distributions, grid approximation, Markov chain Monte Carlo methods, and Bayesian approaches to some specific statistical models (e.g., the multiple linear regression model, ANOVA, contingency table analysis, hierarchical models). Along the way, we will consider additional topics, including null hypothesis significance testing, Bayesian model comparison, Bayesian assessment of null values, and statistical power. Upon completion of this workshop, participants should be able to incorporate Bayesian tools into their own research projects and data analyses.

**FEE:**ICPSR Members, $1400; Non-members, $2800

August 3-5, 2015

An Applied Introduction to Bayesian Methods

**LOCATION:**Chapel Hill, NC

**INSTRUCTOR:**Jeffrey Harden, University of Colorado at Boulder

**DESCRIPTION:**This course will provide an introductory overview of Bayesian methods as they are applied to social science research. We will focus on the two complementary goals of learning the theory behind Bayesian inference as well as practical implementation of several common models in R.

**FEE:**ICPSR Members, $1300; Non-members, $2600

**Four-Week Workshops**

**Session I:**June 22-July 17, 2015

Introduction to Applied Bayesian Modeling for the Social Sciences

**LOCATION:**Ann Arbor, MI

**INSTRUCTORS:**Ryan Bakker, University of Georgia, and Johannes Karreth, University at Albany, State University of New York

DESCRIPTION: This course introduces the basic theoretical and applied principles of Bayesian statistical analysis in a manner geared toward students and researchers in the social sciences. The course begins with a discussion of the strengths of the Bayesian approach for social science data and the philosophical differences between Bayesian and frequentist analyses. Next, the course covers the theoretical underpinnings of Bayesian modeling and provides a brief introduction to the primary estimation algorithms. The bulk of the course focuses on estimating and interpreting Bayesian models from an applied perspective.

**FEE:**ICPSR Members, $2300 (before May 1); Non-members, $4600 (before May 1)

**Session II:**July 20-August 14, 2015

Advanced Bayesian Models for the Social Sciences

**LOCATION:**Ann Arbor, MI

**INSTRUCTORS:**Jeffrey Harden, University of Colorado at Boulder, and Daniel Stegmueller, University of Essex

**DESCRIPTION:**This course covers the theoretical and applied foundations of Bayesian statistical analysis at a level that goes beyond the introductory course. Topics include: Bayesian stochastic simulation (Markov chain Monte Carlo); model checking, model assessment, and model comparison, with an emphasis on computational approaches; Bayesian variants of "workhorse" political science models, such as linear models, models for binary and count outcomes, discrete choice models, and seemingly unrelated regression; and advanced Bayesian models, such as hierarchical/multilevel models, models for panel and time-series cross-section data, latent factor and item response theory (IRT) models, as well as instrumental variable models.

**FEE:**ICPSR Members, $2300 (before May 1); Non-members, $4600 (before May 1)

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