Description
This is an applied regression analysis course in the theory and
application of regression analysis of economic and other social
science data. It is designed to build on the basics of introductory
statistics so that students can apply advanced regression analysis
techniques and demonstrate the ability to do hypothesis testing.
Students develop the necessary skills to build a parsimonious model
that conforms to the assumptions of classical linear regression
(CLR). The course is intended to provide more of a “hands on” than
theoretical approach to quantitative analysis. Students transform
data to test hypotheses using different forms of regression analysis.
This analysis is evaluated for attributes of a good model (parsimony,
identifiability, goodness of fit, theoretical consistency, and predictive
power). During a students’ evaluation of model specification,
they learn how to identify and address violations of (CLR). At the
completion of this course, students will have the ability to per