Introduction to the R Statistical Computing Environment
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Introduction to the R Statistical Computing Environment

My name is Kerem Ozan Kalkan. I am an
Assistant Professor at Eastern Kentucky University. I’m teaching in the
Department of Government. My research includes studies on prejudice, political psychology, and race and ethnicity, and
also comparative politics as well as methods. I teach Introduction to R
Statistical Computing course at ICPSR. R is a open source application of S
programming language. It is a statistical software that is once very popular among
statisticians, now it is gaining popularity among political scientists too.
It is highly flexible, it enables researchers to do their own programming
rather than just limiting themselves to canned programs or point [and] click environments.
It has powerful graphs when compared with other statistical software and it’s
free. It enables researchers to do a lot of stuff using open source packages
written by R users. After introducing students to this language we start
learning about different ways of running models, running statistics. And also
eventually we introduce participants into how to do their own programming
within R so that they do not feel themselves limited to point [and] click
environment available in other software. We also introduce participants into how
to visualize data in R, although briefly. And in the end the course also includes
two lab sessions. So the students, the participants will have opportunity to
practice what we learn in our class in two weeks. The participants in
R class include people from very different backgrounds. I have, for example,
political scientists, sociologists, Social Work, education.
Graduate students, mostly graduate students but I also have some faculty
members in class. Although some participants come with some prior
knowledge of R, we don’t assume that. So we start from the very beginning, we
start from scratch and finish with something that they can use in their
classes at ICPSR Summer Program.

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