Introduction:

This graduate seminar is a continuation of PSCI 7085 "Introduction to Data Analysis. Building upon the general linear model, 7095 explores the assumptions underlying the popular regression model. Additional topics developed during the semester include contemporary statistical techniques designed to deal with a wide variety of data scrutinized by political scientists. Some of these topics include logistic regression, probit, tobit. Maximum likelihood estimation is explored. Approaches to measurement and other research design issues are raised. Additional coursework may be taken to flesh out many of these topics.

Required Textbooks:

D. Gujarati (2002) Basic Econometrics New York: McGraw-Hill.

P. Kennedy (2008) A Guide to Econometrics. 6th Edition. Cambridge, MA: MIT Press.

Recommended Monographs:

W. Berry (1993) Understanding Regression Assumptions. Newbury Park, CA: Sage.

F. Pampel (2000) Logistic Regression: A Primer. Thousand Oaks, CA: Sage.

W. Berry (1984) Nonrecursive Causal Models. Newbury Park, CA: Sage.

J. Kim and C. Mueller (1978) Introduction to Factor Analysis: What It Is and How to Do It. Newbury Park, CA: Sage.

J. Kim and C. Mueller (1978) Factor Analysis: Statistical Methods and Practical Issues. Newbury Park, CA: Sage.

Course Requirements:

Midterm (20%) and Final (25%) examinations. The final exam will be cumulative.

Homework Assignments (15%) and Class Participation (10%)

Research Paper (30%)

Key Dates:

MIDTERM EXAM: Thursday, March 4th, 2010

SPRING BREAK: March 22nd-March 26th, 2010

TERM PAPER: Tuesday, April 27th, 2010

FINAL EXAM: Tuesday, May 4th, 2010, 1:30PM-4:00PM (tentative)