Mailing Address: Department of Statistics and Probability
Michigan State University
East Lansing, MI 48824
Professor of Statistics and Probability
B.A. (Mathematics and Education) Eastern Michigan University (1952)
M.S. (Mathematical Statistics) Purdue University (1954)
PhD (Mathematical Statistics) Purdue University (1957)
Text by the author, "Linear Statistical Models",
John Wiley & Sons, 1995, 450 pages
(From the Back of the Book) "Linear Statistical Models"
emphasizes the geometry of vector spaces because of the intuitive
insights this approach brings to an understanding of the theory.
While the focus is on theory, examples of applications, using
the SAS and S-Plus packages, are included. Prerequisites are familiarity
with linear algebra, and probability at the postcalculus level.
Major topics covered include:
Methods of study of random vectors, incuding the multivariate
normal, chi-square, t and F distributions, central and noncentral.
The linear model and the basic theory of regression analysis and
the analysis of variance
Multiple regression methods, including transformations, analysis
of residuals, and asymptotic theory for regression analysis. Separate
sections are devoted to robust methods and to the bootstrap.
Simultaneous confidence intervals: Bonferroni, Scheffe, Tukey,
Analysis of variance, with two- and three-way analysis of variance.
Random component models, nested designs, and balanced incomplete
Analysis of frequency data through log-linear models, with emphasis
on the vector space viewpoint. This chapter alone is sufficient
for a course on the analysis of frequency data.
An errata list may be obtained by writing, calling or E-Mailing
1999-2000 Academic Year Courses
Statistics 841, Fall Semester
"Linear Statistical Models"
Statistics 231, Spring Semester
"Statistics for Scientists"