Linjuan Qian, Department of Mathematics, Smith College, Northampton, MA
R language, a freely available environment for statistical computing
and graphics is widely used in many fields.
This "expert-friendly" system
has a powerful command language and programming environment, combined with
an active user community. We discuss how R is ideal as a platform to support
experimentation in mathematical statistics, both at the undergraduate and
graduate levels. Using a series of case studies and activities, we describe
how R can be utilized in a mathematical statistics course as a toolbox for
experimentation. Examples include the calculation of a running variance,
maximization of a non-linear function, resampling of a statistic, simple
Bayesian modeling, sampling from multivariate normal and estimation of power.
These activities, often requiring only a few dozen lines of code, offer
the student the opportunity to explore statistical concepts and experiment.
they provide an introduction to the framework and idioms available in this
Keywords: mathematical statistical education, statistical computing
pdf version of paper (published in the November 2004 issue of The American Statistician)
We are grateful to Ken Kleinman and Paul Kienzle for comments on an earlier draft of the manuscript, and for the support provided by NIMH grant R01-MH54693 and a Career Development Fund Award from the Department of Biostatistics at the University of Washington.
for correspondence: Nicholas Horton, Department of Mathematics and Statistics, Smith College, Northampton, MA
Phone: 413-585-3688, fax: 413-585-3786.
visits since September 1, 2004
Last updated May 24, 2006