Quantitative Research Methods II

Catalog description

This second course in quantitative research methods focuses on the tools, techniques, and approaches of hypothesis testing for the purpose of testing competing explanations based on the observed outcomes and interpretation of results. Students will learn the relationship between null and alternative hypotheses, design of experiments, p-values and rejection regions, metrics of fit for both classification and regression problems, multivariate linear and logistic regression analysis, and introduction to time series analysis and structural equation modelling. Students will test datasets for potential violations of the assumptions needed for these methods, including non-normality and multi-collinearity. Students will have guided reading of both classic and state-of-the-art articles. The discussion of the readings will emphasize model development and application. Cases with included datasets will be used for students in projects to formulate and then test multiple possible hypotheses.