Methods of Policy Analysis

Sample courses for Methods of Policy Analysis focus

Please note:
These are an example of the courses that would fulfill this complimentary policy requirement.
We cannot guarantee when or if these courses will be offered.

Political Science

581. Statistics for Social Research. (4)

Provides intensive experience and lab instruction in quantitative techniques employed in political science research, including descriptive statistics, statistical inference, hypothesis testing, measures of central tendency, crosstabulation, differences between means, bivariate regression, correlation and multivariate analysis. Required of M.A. and Ph.D. students.

  1. Advanced Statistical Analysis for Social Science Research. (3)

Focuses on a variety of advanced econometric methods. Beginning with a review of matrix algebra and math for the social sciences, the course provides an in-depth examination of multiple regression and more advanced econometric models. Required for Ph.D. students. 


  1. Advanced Social Statistics I. (3)

Soller, Thomas 

Examines theory (assumptions, properties of estimators) and application of multiple regression. Introduces matrix notation and generalized least squares.

Prerequisite: 481L.

  1. Advanced Social Statistics II. (3) 


Additional methods for quantitative social research: regression diagnostics, logit and Poisson regression, principal components, correspondence analysis. 

  1. Methods of Social Research I. (3)

Analytical examination of traditional methodological issues including measurement, experimental design, sampling, theory construction, role of statistics and nature of probability.


  1. Statistics and Introduction to Econometrics. (3)

Discrete and continuous probability distributions; expectations; joint, conditional marginal distributions; hypothesis testing; least squares estimators; violation of the least squares principle. Econometric software with applications.

Restriction: admitted to M.A. Economics or Ph.D. Economics. 

  1. Econometrics I. (3)

Theory and applications: ordinary and generalized least squares, hypothesis testing, dummy variable and distributed lag models; simultaneous equation and two stage least square models; forecasting. Emphasis on computer modeling.


486L / 586L. Applications of GIS. (3)

Selected applications of Geographic Information Systems, including anthropology, business, crime, ecology, engineering, health, planning, water resources and others. Covers analytical techniques specific to selected applications. Fee required. 

487L / 587L. Spatial Analysis and Modeling. (3)

Spatial analysis and modeling techniques using Geographic Information Systems. Includes a lab component that covers the use of GIS and other software to carry out analysis projects. Fee required


440 / 540. Regression Analysis. (3)

Simple regression and multiple regression. Residual analysis and transformations. Matrix approach to general linear models. Model selection procedures, nonlinear least squares, logistic regression. Computer applications.

476 / 576. Multivariate Analysis. (3)

Tools for multivariate analysis including multivariate ANOVA, principal components analysis, discriminant analysis, cluster analysis, factor analysis, structural equations modeling, canonical correlations and multidimensional scaling.