Instructor: Rebecca Nugent
Course Description
This course will familiarize students with the R environment for statistical computing.
It is intended for graduate students in the social sciences and should provide background knowledge required in
quantitative courses in social sciences, especially those provided by CS&SS. It does not require knowledge of advanced
statistics methods but will not cover them in any detail. We will cover the basics of organizing, managing, and manipulating social
science data; demonstrate basic applications; introduce programming; and discuss links to other major statistical packages.
There will be a lecture once per week in a computer-integrated classroom. Weekly assignments will require students to work through
examples and produce R output. In addition, there will be an optional lab session in a computer laboratory where students can learn "hands-on" and
practice using R with the instructor available. The final exam will ask the students to demonstrate several basic functions in R and answer questions about
and analyze a real-world data set provided by the instructor.
R is a freely available, multi-platform (Windows, Linux, Unix, MAC OS), and powerful program for analysis and graphics similar to S-PLUS.
It provides a programming language that can easily be extended by the user. It also allows the user to produce publication-quality graphics.
It is ubiquitous in statistical/quantitative courses in departments around the country.
R Project
Textbook:
Introductory Statistics with R, Peter Dalgaard, Springer-Verlag