Statistical Analysis and Inference for Political Scientists
The course addresses topics in statistical inference and regression analysis. It aims to provide an understanding of why and how different statistical methods are used and also applies some formal tools (i.e. combinatorics, probability functions and parameters, and matrix algebra) to develop testing procedures or problem-solving heuristics. The first part of the course focuses on the application of probability concepts and statistical tests. The second part involves the use of linear, non-linear and multivariate regression and correlation techniques and deals with potential problems in the data. The goal is to provide an understanding of statistical methods to (i) conduct statistical tests in a variety of applications, (ii) model and quantify dependencies between variables, and (iii) understand more advanced statistical concepts to support independent academic work. The course uses a dataset from the Canadian Census containing social, economic and immigration variables to test hypotheses about the Canadian city-region system. Along with a mathematical introduction to various methods, their application through the use of statistical computer packages (i.e. SPSS) is also part of the course.
Format and Requirements
One three-hour seminar/computer lab per week with opportunity for in-class discussion. The course work consists of the following components: several assignments, class participation and a final take-home exam.