Applied Regression Analysis 1

Term: 
Fall
Credits: 
2.0
Type: 
Elective
Course Description: 

Elective Course

This course takes a hands-on approach to applied statistics, aiming at giving students the capacity to be intelligent and critical consumers and producers of regression analysis which is so widely used in the world of research and evidence-based policy making.

The first part of this course (Fall 2016) deals with the basics of regression analysis. It aims at making student at ease with the application of statistical reasoning to real-world problems using statistical software to understand probability, manipulate data, generate descriptive statistics, understand correlation, test hypotheses for uni- and multivariate regressions, interpret results graphically and generate regression diagnostics. If time allows, we will explore more advanced statistical techniques and the pitfalls associated with statistical research.

Learning Outcomes: 

This course covers the basics of regression analysis. Students will learn the basic of statistical theory. This includes being able to understand basic concepts of probability, estimation of least square regression and hypothesis testing. Students will thus be able to interpret regression output and evaluate policy research using regression analysis. The course takes a hands-on approach that will enable students to get comfortable with statistical software and give them skills to become independent users of statistical software.

Assessment: 

Five homeworks (10% each), 10% class participation and one final exam/homework (40%).

Prerequisites: 

Students are required to have attended Prof. Kemmerling's course, Quantitative Methods. Statistics is no harder than other classes at SPP and CEU, but the class is very cumulative so falling behind is not recommended. The implication is that you should be prepared to work hard and not to hesitate to ask questions. The upside is that the course confers important skills for the labor market.