Social scientific analytical skills are transforming many sectors— from business and journalism
to public policy and health care, among others. Data analysis for quantitative social science will
help students develop the tools they need to be informed participants and active leaders in these
data-driven sectors. The course introduces statistical techniques used in the social sciences and
prepares students for more advanced statistics and programming coursework. Critical thinking
will be emphasized using topics such as data analysis, data visualizations, and more. The content
of the course can be divided into two sections: (1) managing data in the R statistical language -
which will cover the basics of description, visualization, and inferential statistics (2)
characterizing statistical uncertainty across various data forms from both a small and large
sample perspective and understanding the basic linear model.