Statistical Methodology

3 Credits · Level: Graduate, Undergraduate

This course is designed to provide students with a solid background in introductory and intermediate level statistical methods. The class will cover the core components of empirical research, basic univariate statistics, bivariate analysis, and OLS regression techniques. It will emphasize the process of conducting empirical research employing a social scientific approach. Concepts, such as levels of measurement, probability theory, and hypothesis testing, will be covered. Statistical methods can be used in conjunction with data from a wide range of sources, including political, communications, economic data, census data, and content data to name but a few. Major data repositories can be accessed for use in research, including the Interuniversity Consortium for Political and Social Research (ICPSR), the Roper Center, and the Pew Research Center. Students also will have the opportunity to collect their own data if they so choose. The class takes a practical, applied approach to using statistics for academic research, policy reports, data journalism, and other applications. We will use a hands-on method for learning statistical techniques. Students will work with R, a widely used programming language used for statistical analysis. R is an open source software that is freely available for download from the Comprehensive R Archive Network (CRAN). Weekly exercises will be assigned to facilitate learning of the statistics. The final project for the course will be a data analysis paper on a topic of your choice. No prior background in statistical methods is required prior to taking this course.