PSCI 2075: Intro to Quantitative Research Methods
This course is our large introductory class to quantitative research methods. It is a required course in political science and relates to research classes used for entry to business and social science. We cover statistics, the R computing environment, bivariate regression, multivariate regression and the visual display of quantitative information.
Learning Objectives
- Develop confidence working with quantitative data and quantitative visualization;
- Develop a moderate adequacy working with statistical applications, especially the R computing environment;
- Learn about statistical properties, including descriptive statistics, statistical distributions and statistical inference;
- Develop an ability to plot and interpret statistical findings, especially statistical findings related to social science applications;
- Develop an ability to write reports about statistical findings. This does not just mean restating statistical test results; it means using prose to explain findings to non-technical audiences;
- Develop confidence with respect to trouble-shooting statistical software.
In this course, you will
Learn to work on a dataset in an area that interests you;
Learn to see how quantitative and qualitative data differ from each other;
Present on a topic (using a dataset that interests you) to your peers.
Srinivas Parinandi
Srinivas.Parinandi@Colorado.edu
Srinivas Parinandi is an Associate Professor in political science at the University of Colorado at Boulder. They research American political institutions with a focus on two general questions of interest: how the design of regulation influences policy outcomes and how institutional characteristics condition the spread or diffusion of policy. They primarily study the U.S. states with an emphasis on energy and economic policy and their work heavily uses spatial econometric modeling. Their research has been published at Energy Policy, the Journal of Public Policy, and State Politics and Policy Quarterly. Additionally, their dissertation was recognized by the American Political Science Association for being the best dissertation in the field of state politics in 2016.