Statistics and Data with R (eBook, PDF)
An Applied Approach Through Examples
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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 accessi...
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:
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.
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