R, an Open Source software, has become the "de facto" statistical
computing environment. It has an excellent collection of data
manipulation and graphics capabilities. It is extensible and comes
with a large number of packages that allow statistical analysis at
all levels - from simple to advanced - and in numerous fields
including Medicine, Genetics, Biology, Environmental Sciences,
Geology, Social Sciences and much more. The software is maintained
and developed by academicians and professionals and as such, is
continuously evolving and up to date. "Statistics and Data with R"
presents an accessible guide to data manipulations, statistical
analysis and graphics using R.
Assuming no previous knowledge of statistics or R, the book
includes: A comprehensive introduction to the R language. An
integrated approach to importing and preparing data for analysis,
exploring and analyzing the data, and presenting results. Over 300
examples, including detailed explanations of the R scripts used
throughout. Over 100 moderately large data sets from disciplines
ranging from Biology, Ecology and Environmental Science to
Medicine, Law, Military and Social Sciences. A parallel discussion
of analyses with the normal density, proportions (binomial), counts
(Poisson) and bootstrap methods. Two extensive indexes that include
references to every R function (and its arguments and packages used
in the book and to every introduced concept.
An accompanying Wiki website, http: //turtle.gis.umn.eduincludes
all the scripts and data used in the book. The website also
features a solutions manual, providing answers to all of the
excercises presented in the book. Visitors are invited to
download/upload data andscripts and share comments, suggestions and
questions with other visitors. Students, researchers and
practitioners will find this to be both a valuable learning
resource in statistics and R and an excellent reference book.
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