Christopher A Adolph
POL S 503
Theory and practice of likelihood inference. Includes probability modeling, maximum likelihood estimation, models for binary responses, count models, sample selection, and basis time series analysis. Offered: jointly with CS&SS 503.
This course continues the graduate sequence in quantitative political methodology, focused particularly on fitting, interpreting, and refining the linear regression model. Our agenda includes gaining familiarity with statistical programming via the popular R environment, developing clear and informative graphical representations of regression results, and understanding regression models in matrix form. More advanced topics will be covered as time and student interests permit.
Student learning goals
General method of instruction
It is desirable for students to have taken the introductory course in the sequence (Political Science 501), but any prior course on basic social statistics and linear regression should suffice.
Class assignments and grading