Course Offerings by term

Introduces the tools of statistical analysis. Combines theory with extensive data collection and computer-assisted laboratory work. Develops an attitude of mind accepting uncertainty and variability as part of problem analysis and decision-making. Topics include: exploratory data analysis and data transformation, hypothesis-testing and the analysis of variance, simple and multiple regression with residual and influence analyses.

This project-based course introduces data science by looking at the whole cycle of activities involved in data science projects. Students will learn how to think about problems with rigor and creativity, ethically applying data science skills to address those problems. The course project will address the theoretical, mathematical and computational challenges involved in data science.

Familiarizes students with several types of multivariate statistics methods with respect primarily to applications and interpretations in the area of social sciences. This course will cover the data-analysis concepts and procedures used in applied and experimental psychology, economics, business and in general in social sciences. Emphasis will be given to the qualitative interpretation and manipulation of mathematical and statistical concepts, showing the students their effectiveness through concrete applications. Students will use appropriate software packages for labs and projects.

Topics vary by semester