Perspectives on society, culture and social interaction. Topics may include the self, emotions, culture, community, class, race and ethnicity, family, gender and economy. Restrictions: first-years and sophomores only. Open to juniors and seniors with permission of the course director. Enrollment limited to 30.

Perspectives on society, culture and social interaction. Topics may include the self, emotions, culture, community, class, race and ethnicity, family, gender and economy. Restrictions: first-years and sophomores only. Open to juniors and seniors with permission of the course director. Enrollment limited to 30.

Perspectives on society, culture and social interaction. Topics may include the self, emotions, culture, community, class, race and ethnicity, family, gender and economy. Restrictions: first-years and sophomores only. Open to juniors and seniors with permission of the course director. Enrollment limited to 30.

Perspectives on society, culture and social interaction. Topics may include the self, emotions, culture, community, class, race and ethnicity, family, gender and economy. Restrictions: first-years and sophomores only. Open to juniors and seniors with permission of the course director. Enrollment limited to 30.

This one-semester course leverages students’ previous coursework to address a real-world data analysis problem. Students collaborate in teams on projects sponsored by academia, government or industry. Professional skills developed include: ethics, project management, collaborative software development, documentation and consulting. Regular team meetings, weekly progress reports, interim and final reports, and multiple presentations are required. Open only to Statistical and Data Science majors. Prerequisites: SDS 192, SDS 291 and CSC 111.

Epidemiology concerns the distribution and determinants of disease in human populations, while biostatistics focuses on the development and application of statistical methods to a wide range of topics in biology, medicine and public health. This course focuses on foundational concepts in epidemiology, including measures of association and common epidemiological study designs, and statistical methods for public health data.

(Formerly MTH 291/ SDS 291). Theory and applications of regression techniques: linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Students who have completed SDS 100 in a previous semester need not repeat it. Corequisite: SDS 100.

(Formerly MTH 291/ SDS 291). Theory and applications of regression techniques: linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Students who have completed SDS 100 in a previous semester need not repeat it. Corequisite: SDS 100.

(Formerly MTH/SDS 290). A survey of statistical methods needed for scientific research, including planning data collection and data analyses that provide evidence about a research hypothesis. The course can include coverage of analyses of variance, interactions, contrasts, multiple comparisons, multiple regression, factor analysis, causal inference for observational and randomized studies and graphical methods for displaying data. Special attention is given to analysis of data from student projects such as theses and special studies. Statistical software is used for data analysis.