251 - 260 of 308 results for: POLISCI

Machine learning---the use of algorithms to classify, predict, sort, learn and discover from data---has exploded in use across academic fields, industry, government, and non-profit. This course provides an introduction to machine learning for social scientists. We will introduce state of the art machine learning tools, show how to use those tools in the programming language R, and demonstrate why a social science focus is essential to effectively apply machine learning techniques. Applications of the methods will include forecasting social phenomena, the analysis of social media data, and the automatic analysis of text data. Political Science 150A or an equivalent is required. (Prerequisite 150A/355A)

Causal inference methods have revolutionized the way we use data, statistics, and research design to move from correlation to causation and rigorously learn about the impact of some potential cause (e.g., a new policy or intervention) on some outcome (e.g., election results, levels of violence, poverty). This course provides an introduction that teaches students the toolkit of modern causal inference methods as they are now widely used across academic fields, government, industry, and non-profits. Topics include experiments, matching, regression, sensitivity analysis, difference-in-differences, panel methods, instrumental variable estimation, and regression discontinuity designs. We will illustrate and apply the methods with examples drawn from various fields including policy evaluation, political science, public health, economics, business, and sociology. Political Science 150A and 150B or an equivalent is required.

An introduction to noncooperative game theory through applications in political science. Topics will include the Hotelling-Downs model, the probabilistic voting model, political bargaining models and political agency models, among others.

A continuation of Formal Theory I covering advanced topics, including classical political economy, comparative institutions, theories of conflict and cooperation, dynamic political economy, and the new behavioral political economy.

The importance of sample surveys as a source of social science data including public opinion, voting, welfare programs, health, employment, and consumer behavior. Survey design, sampling theory, and estimation. Nonresponse, self-selection, measurement error, and web survey methods. Prerequisite: 350B or equivalent.

Covers advanced computational and statistical methods for collecting and modeling large-scale data on politics. Topics will include automated and computer-assisted methods for collecting, disambiguating, and merging unstructured data (web-scraping, identity resolution, and record-linkage), database management (SQL, data architecture), data-reduction techniques for measuring the political preferences for large numbers of individuals, topic models applied to political text/speech, and social network analysis for mapping relationships and identifying influential actors.

May be repeated for credit.