Overall Teaching Effectiveness Score: 4.95/5
The goal of this course is to provide an introduction to econometrics for policy analysts. The focus of the class will be on applied data analysis to practical problems. We will discuss some basics of econometric theory to support your understanding of the applications of these techniques. In the first part of the semester, we will introduce regression analysis and the assumptions underlying it. In the later part of the semester, we will see extensions of this basic idea: time series and panel regression, regression with a limited dependent variable, instrumental variables regression, and experiments. After this class you should be able to: 1. Understand basic empirical research in the social sciences. 2. Understand the theory behind basic econometric techniques. 3. Perform basic empirical analysis on social and political behavior.
(Taken from the University of Pittsburgh Course Catalog)
Overall Teaching Effectiveness Score: 4.99
Introduction to quantitative methods is a foundation course that provides an overview of statistical methods and hands-on applications to managerial decision-making in the public sector. Understanding statistical analysis and being able to work with data are important competencies of professionals in public policy and administration. Course topics include program evaluation, data collection and measurement in public policy and administration, descriptive statistics, hypothesis testing, processes for selecting statistical tests and assessment of statistical assumptions, measures of association and other bivariate statistics, index variable construction, regression analysis, and an overview of selected other statistical and quantitative methods applied to problems of public administration. Students get hands-on experience through the use of a statistical analysis tool. Recognizing the social, political, and economic context of data collection, analysis, and reporting practices in the public sector, this course also discusses the ethics of data analysis and information technology policy and management.
(Taken from the University of Pittsburgh Course Catalog)
This course is designed to provide you with an overview of the major theories and empirical approaches to the study of intergroup attitudes. While doing so, we will spend a considerable amount of time in understanding, dissecting, and extending the methodologies employed in the study of intergroup attitudes. Since most of the debates on race and ethnicity revolve around measurement, we will focus on different methods in scaling and dimensional analyses, and their applications in the corresponding literature. Each week will begin with a theoretical discussion, continue with methodological lectures, and end with replication/extension of existing studies. The course assumes a basic knowledge of statistics, and familiarity with linear regression (concurrent enrollment in Regression I should be sufficient in the event of no prior knowledge). As we focus on measurement theories, participants are strongly encouraged to enroll in “Scaling and Dimensional Analysis” or “Multivariate Statistical Methods: Advanced Topics” or both.
Detailed OMET information available upon request.