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.
About the Author
In the 30 years he has been teaching, Professor Cohen has taught a range of subjects from ecology and computer programming to statistics and data analysis with R. The recipient of numerous research grants, he is also the author and co-author of dozens of articles published in a wide range of journals, and has contributed chapters to a number of edited texts. He has also edited and authored four books.
Features
Over 300 examples, including detailed explanations of the R scripts used throughout.
Over 100 moderately large data sets from various fields, including, ecology, environmental sciences, medicine, biology and social sciences.
Two extensive indexes that include references to every R function
