Multivariate Statistics for the Social Sciences

Catalog description

This graduate level course focuses on developing, interpreting, and presenting the results from theoretically-informed multivariate regression analyses. The course begins by reviewing basic statistical concepts, descriptive and inferential statistics, ways to handle missing data, bivariate ordinary least squares (OLS) regression, and basic features of statistical software programs. The course proceeds with concepts of multivariate regression, and covers issues such as nonlinearity, outliers, and interaction terms. The final section covers methods for handling complex survey data and estimation techniques for binary, nominal, ordinal, and count outcomes. Students will learn how to choose the best method for the research question; where to locate and how to extract secondary survey data; and how to accurately, clearly, and succinctly describe analytic methods, interpret results, and report findings.