Focusing on user-developed programming, An R Companion to Linear
Statistical Models serves two audiences: those who are familiar
with the theory and applications of linear statistical models and
wish to learn or enhance their skills in R; and those who are
enrolled in an R-based course on regression and analysis of
variance. For those who have never used R, the book begins with a
self-contained introduction to R that lays the foundation for later
chapters. This book includes extensive and carefully explained
examples of how to write programs using the R programming language.
These examples cover methods used for linear regression and
designed experiments with up to two fixed-effects factors,
including blocking variables and covariates. It also demonstrates
applications of several pre-packaged functions for complex
computational procedures.
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