Introduction to the R Statistical Computing Environment
Instructor(s):
- David Armstrong, University of Wisconsin at Milwaukee
The statistical programming language and computing environment S has become the de facto standard among statisticians. The S language has two major implementations: the commercial product S-PLUS, and the free, open-source R, which is the subject of these introductory lectures. A statistical software "package," such as SPSS, is primarily oriented toward combining instructions with rectangular case-by-variable datasets to produce (often voluminous) output. Such packages make it easy to perform routine data analysis tasks, but they make it relatively difficult to do things that are innovative or nonstandard, or to extend the built-in capabilities of the package.
In contrast, a good statistical computing environment makes routine data analysis easy and also supports convenient programming. R fulfills both of these requirements and users can readily write programs that add to its already impressive facilities. R is also particularly capable in the area of statistical graphics.
These lectures provide a basic introduction to the R environment. Specific topics will include: Elements and rules of the R language; R functions and objects; statistical models in R, including linear and generalized linear models; data manipulation; constructing statistical graphs; and using R packages. The overall objective is to provide some facility in the use of R, to a level that enables participants to employ this software for assignments and projects in other Summer Program courses.
Fees: Consult the fee structure.
Tags: R, open-source
Course Sections
Section 1 Location: ICPSR -- Ann Arbor, MI Date(s): June 24 - July 11 Time: 5:15 PM - 6:15 PM Instructor(s):
Syllabus: |