Introduction to Data Analysis (Siena Ph.D. 2013-2014)

Introduction to Data Analysis
Fall semester 2013-2014

Teacher: Federico Russo (

Course Description:
This course provides an in-depth introduction to ordinary least squares (OLS) regression analysis and its use in political science. This course represents an important first step towards being able to interpret, criticize, and conduct regression analysis of political data. Much of the course will focus on the assumptions underlying OLS regression, the implications of violations of these assumptions, and solutions to these violations.
At the end of this course, students should:
1. Have a thorough understanding of the assumptions, limitations, extensions, and applications of regression analysis in political science.
2. Being able to read and critically assess political science articles that make use of regression analysis.
3. Use the tools of regression analysis to test hypotheses and appropriately model political phenomena.

Required text:
Damodar N. Gujarati, Basic Econometrics with Applications, 4th o 5th edition.

Tentative schedule

the content of the lectures may change depending on how the class react to the course. For instance, we can consider covering more advance topics such as models for qualitative or count dependent variable.

  • Week 1 16/10/2013 Regression analysis: a review of the two variables model

Required readings: Chapter 1 and 2

  • Week 2 23/10/2013 Estimation

Required readings: Chapter 3 and 4

  • Week 3 30/10/2013 Hypotheses Testing

Required readings: Chapter 5

  • Week 4 06/11/2013 Model fit, predicted values, and residuals

Required readings: Chapter 7, Sections 7.5-7.8

  • Week 5 13/11/2013 An introduction to Multiple regression

Required readings: Chapter 8

  • Week 6 20/11/2013 Dummy variables

Required readings: Chapter 9

  • Week 7 27/11/2013 Interaction models

Required readings: Brambor, Thomas, William Roberts Clark, and Matt Golder. 2006. “Understanding Interaction Models: Improving Empirical Analyses.” Political Analysis 14(1):63-82.

  • Week 8 04/12/2013 Multicollinearity and Heteroscedasticity

Required readings: Chapter 10 and 11

  • Week 9 11/12/2013 Autocorrelation and Specification Bias

Required readings: Chapter 12 and 13

  • Week 10 18/12/2013 Discussion of students’ final research papers.


Your grade will be determined through the following means:
1. Small homework assignments that require you to apply the concepts and tools learned in class to real political data. These assignments will constitute 50% of your grade for the course.

2. A final research paper in which you identify an interesting research question, provide a theoretical answer to the question you pose, test your theoretical expectations by utilizing OLS regression to analyze relevant data (while demonstrating sensitivity to the assumptions of OLS), and interpret the results. Your paper will represent 50% of your course grade.



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