Module description
The module is about regression analysis, which is the most common statistical technique. It is designed to provide students with the skills and knowledge needed to read the results of regression analysis, and to use the technique to conduct their own political science research. I do not focus on mathematical demonstrations; I focus on the logic and intuition behind regression analysis.
I assume that students have some previous knowledge of basic statistics, which includes descriptive statistics, principles of inference, and OLS regression. I also assume that students have some previous knowledge of basic algebra, and familiarity with the software package Stata.
The module combines lectures and seminars. In each lecture, I introduce a new regression technique. Then, I teach how to apply this technique with Stata during the seminar.
Assessment details
2,000-word research paper (40%) & 3,000-word research paper (60%)
Educational aims & objectives
This undergraduate module is designed to provide students with particular analytical tools to better understand the problems and questions studied in political sciences. The main goal is to train students in regression analysis, the dominant quantitative technique used in empirical studies.
This module assumes some previous basic knowledge of regression analysis, inferential statistics and some basic school algebra like derivation. The module, however, is not designed to learn the mathematical apparatus behind regression analysis. Rather, the emphasis will be on understanding the logic and intuition behind regression. In this regard, the module is highly dependent on particular examples from political science.
The module will combine lectures with practical sessions at the computer lab. One of the main goals of this course is that students are able to produce their own research using statistics by the end of the module. For this reason, there is a strong emphasis in the practical component of the course. Students will learn the different questions related to regression techniques at the theoretical level during the lectures. In the pc-lab, students will learn how to implement such theoretical knowledge by using STATA, a major statistic software. By the end of the module, students are expected to use STATA at an intermediate level.
Learning outcomes
This module teaches students how to conduct empirical research doing regression analysis. The module aims to:
- Consolidate knowledge on statistical inference.
- Familiarize students with linear regression analysis and its assumptions.
- Teach students to interpret regression coefficients using different types of variables and interactions.
- Teach students how to identify and correct some common violation of OLS assumptions
- Teach the basics of logistic regression analyses.
- Teach students how to present and display statistical results.
- Enhance students' existing skills with the statistical package STATA.
By the end of this module students should be able to:
- Know how to test a theory using regression analysis
- Structure data in order to conduct empirical research
- Apply different models and interactions between variables in order to test the relationship between different variables
- Use STATA at an intermediate level.