Graduate Program (& Advanced Certificate) Status
Why some people vote and others do not? What accounts for people's voting choice? Does politician's gender influence voting choice? How can we predict election outcomes? How can we detect election fraud? How can we measure and explain political polarization? This course provides an introduction into quantitative research methods and will teach students how to address these and other political science questions by analyzing quantitative data. The course introduces basic principles of statistical inference and programming skills for data analysis using R. Unlike traditional introductory statistic classes this class starts with data analysis from the beginning using examples from published political and social science research. The goal is that students learn how to analyze data and conduct their own research, as well as how to critically evaluate statistical claims in academic research and the media. The class closely follows the lecture book by Kosuke Imai (2017) - "Quantitative Social Science. An Introduction" and adopts teaching material, including problem sets, data sets and lecture slides developed by Kosuke Imai and Matthew Blackwell specifically for material covered in this lecture book. You can find further information on the lecture book and the accompanying materials here: \href{http://qss.princeton.press}{\textit{http://qss.princeton.press}} .
We will assume a basic familiarity with high-school algebra and a working knowledge of computers (e.g. downloading and installing software). Previous experience with statistical methods and computing (e.g. Stata, R, Python) is helpful, but not required.
No matter your background, you should be prepared to engage with the class material (readings and homework assignments) on a regular, almost daily basis. Furthermore, you should feel comfortable when doing data analysis using statistical software. We will guide you through that process, but it may be unfamiliar and therefore challenging. You should expect the course to be time consuming. Please take this into account when you plan your schedule.
