POLS 1600

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This class is an introduction to applied statistics as practiced in political science. It is computing intensive, and, as such, will enable students to execute basic quantitative analyses of social science data using the linear model with statistical inference arising from re-sampling and permutation based techniques as applied in the R statistical computing language (https://cran.r-project.org/) with RStudio (https://www.rstudio.com/.) By the end of the course, a successful student will be able to find social science data online, download it, analyze it, and write about how the analyses bear on focused social science or policy questions.

Download a recent syllabus.

Paul Testa
Paul Testa
Assistant Professor of Political Science

My research interests include distributed robotics, mobile computing and programmable matter.