Statistics for Public Policy I

Catalog description

This course provides a foundation for both evaluating and conducting quantitative analysis of public policy. The first third of the course examines foundational issues of conducting quantitative analysis of public policy. It does so by reviewing the basic elements of the foundations of such analysis, including the logic of scientific analysis, issues of philosophy of science, measurement theory (validity and reliability), and the elements of research design associated with internal and external validity as they apply to designs common in policy analysis. The remaining two-thirds of the course sequentially examines the use of basic statistical techniques in public policy analysis, including descriptive statistics (frequency distributions, measures of central tendency, and measures of dispersion), probability (the normal, binomial, poisson and other probability distributions), inferential statistics (hypothesis testing, estimating population proportions, and testing differences between two groups), and the analysis of nominal and ordinal data (constructing and analyzing simple and control contingency tables). The course provides a foundation for studying more advanced quantitative analysis techniques, such as regression analysis and related techniques. Throughout the course, the several statistical analysis techniques will be examined through their application to typical public policy problems. The goal of the course is to enable students to become familiar with the basic elements of quantitative analysis of public policy, to enable them to evaluate statistical evidence bearing on public policy decisions, and to conduct basic statistical analysis on public policy questions, all of which are essential for professional careers in public policy.