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R is now the most widely used statistical package/language in
university statistics departments and many research organisations.
Its great advantages are that for many years it has been the
leading-edge statistical package/language and that it can be freely
downloaded from the R web site. Its cooperative development and
open code also attracts many contributors meaning that the
modelling and data analysis possibilities in R are much richer than
in GLIM4, and so the R edition can be substantially more
comprehensive than the GLIM4 edition. This text provides a
comprehensive treatment of the theory of statistical modelling in R
with an emphasis on applications to practical problems and an
expanded discussion of statistical theory. A wide range of case
studies is provided, using the normal, binomial, Poisson,
multinomial, gamma, exponential and Weibull distributions, making
this book ideal for graduates and research students in applied
statistics and a wide range of quantitative disciplines.
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