ASTK15638U  SEMINAR: Advanced Quantitative Methods in Political Science

Volume 2015/2016
Content

This course introduces graduate students to quantitative methods in political science. During the first half of the course, the course focuses on linear regression models. The topics covered include discussions of the mathematical bases for such models, their estimation and interpretation, model assumptions and techniques for addressing violations of those assumptions, and topics related to model specification and functional forms. During the second half of the course, students will be introduced to likelihood as a theory of inference, including models for binary and count data.

The course will be structured according to the following headlines:

  1. Introduction
  2. Visualizing Data.
  3. Getting data from the Web
  4. Fundamentals of Probability.
  5. Sampling and Statistical Inference
  6. Linear Regression:
  7. Linear Regression: Interpreting Substantive Effects via the Simulation Method
  8. Linear Regression: Diagnostics
  9. Non-linear probability models - The likelihood theory of statistical inference
  10. Binary data
  11. Multinomial Choice
  12. Count data
  13. Missing Data
  14. Conclusion

The course will primarily support and use two software packages in the course: R and Stata. For the majority of problems, R will be the software package of choice.

Learning Outcome

The main goals of this course are to enable students to develop sound critical judgment about quantitative studies of political problems, to interpret quantitative analyses in published work, to understand the logic of statistical inference, to recognize and understand the basics of the linear regression model.

 

Since the aim of the course is to enable students to conduct their own statistical analysis, the course is a good basis and starting point for any other project in the program involving statistical methods. In addition, the course is highly relevant for any students who aims for a career, which involves data analysis.

The course will not use a single textbook. Selected readings will be made available at the start of the course. In general the following books are useful for this course:

 

Wooldridge, Jeffrey. 2009. Introductory Econometrics: A Modern Approach. 4th edition. South-Western College Pub.

 

Kennedy, Peter. 2008. A Guide to Econometrics. 6th edition. Blackwell Publishing.

 

Fox, John. 2008. Applied Regression Analysis and Generalized Linear Models. 2nd edition. Sage.

 

King, Gary. 1989. Unifying Political Methodology. Ann Arbor: University of Michigan Press.

There is formally no prerequisite for this course except an open mind and a good command of high school algebra.
The course is divided into a lecture-style seminar (Multivariate Analyses) and a computer lab session (Tutorial Multivariate Analyses). During the computer lab session, students will apply the statistical models introduced in the lecture. The lab sessions will be devoted to learning the various commands in R and Stata and apply the statistical models from the lecture to selected political science data sets. The data sets that we will use cover the major fields in political science.
Credit
7,5 ECTS
Type of assessment
Written assignment
Indidividuel seminar assignment
Marking scale
passed/not passed
Censorship form
No external censorship
Criteria for exam assesment

Passed/Not-passed

  • Category
  • Hours
  • Class Instruction
  • 28
  • Total
  • 28