STATS C216/C116: Social Statistics

This course is designed for social sciences graduate students and advanced undergraduate students seeking training in data issues and methods employed in social sciences.

The Bruin Learn course page is here.

A detailed description of the class is available here.

Motivation and Synopsis

Statistics C116/C216 is a second course in social statistics and will focus on Bayesian statistical analysis. It will cover the principles of Bayesian statistics, Bayesian data analysis and modeling. In particular it will develop the ideas in the context of linear regression, its non-linear generalizations, and hierarchical models. While the idea and principles are general, all applications and models will be chosen from those most relevant to the social sciences.

This course is designed for graduate students majoring in Statistics, the Social Sciences and advanced undergraduate students who are planning to attend graduate school.

This course is most appropriate for student seeking additional training in the application of Bayesian statistics to data and are looking for an introductory course that advances rapidly. The ultimate goal is to equip students with the analytical and programming skills necessary to address social statistics problems within the Bayesian paradigm based on current data and technologies.

The course has various perspectives:

•  It focuses on conceptual understanding of the Bayesian statistics.
•  It focuses on conceptual understanding of the the primary models used in social statistics.
•  It involves the analysis of real-data.
•  It involves implementing the methods using freely available software.

The course will involve the practical application of the ideas of statistical computing and their implementation through statistical software, particularly R. As statistical computation is essential for many of the modeling approaches, expertise will need to be developed.