| Description |
1 online resource : illustrations (some color) |
|
data file rda |
| Bibliography |
Includes bibliographical references and index. |
| Summary |
"The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition introduces the advantages of the R environment, in a user-friendly format, to beginners and intermediate users in a range of disciplines, from science and engineering to medicine and economics. The format enables it to be either read as a text, or dipped-into as a reference manual. This third edition: Uses RStudio, instead of native R, which provides a far more user-friendly environment for those new to R Revised to account for the evolution of R over the past seven years including new developments and modern teaching methods Takes readers from a starting point of no knowledge of R or programming in general, and very little knowledge of statistics, through to advanced techniques Provides a comprehensive introduction to most areas of statistics used by non-statisticians, with minimal mathematics Explains concepts and how to implement them in R with in-depth discussion on how to interpret the resulting output Contains a large number of worked examples in R Companion website available with downloadable datasets, slides and other teaching materials Introduces modern ideas in handling data in R, e.g. the tidyverse. Features full colour text and extensive graphics throughout Features a fully revised and updated bibliography and reference section."-- Provided by publisher. |
| Contents |
Chapter 1 Getting Started -- Chapter 2 Technical Background -- Chapter 3 Essentials of the R Language -- Chapter 4 Data Input and Dataframes -- Chapter 5 Graphics -- Chapter 6 Graphics in More Detail -- Chapter 7 Tables -- Chapter 8 Probability Distributions in R -- Chapter 9 Testing -- Chapter 10 Regression -- Chapter 11 Generalised Linear Models -- Chapter 12 Generalised Additive Models -- Chapter 13 Mixed-Effect Models -- Chapter 14 Non-linear Regression -- Chapter 15 Survival Analysis -- Chapter 16 Designed Experiments -- Chapter 17 Meta-Analysis -- Chapter 18 Time Series -- Chapter 19 Multivariate Statistics -- Chapter 20 Classification and Regression Trees -- Chapter 21 Spatial Statistics -- Chapter 22 Bayesian Statistics -- Chapter 23 Simulation Models |
| Subject |
R (Computer program language)
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Mathematical statistics -- Data processing.
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R (Langage de programmation) |
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Statistique mathématique -- Informatique. |
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Mathematical statistics -- Data processing |
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R (Computer program language) |
| Added Author |
Harden, Simon, author.
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Crawley, Michael J., author.
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| Other Form: |
Print version: Jones, Elinor R book Third edition. Hoboken, NJ : Wiley, 2022 9781119634324 (DLC) 2022008352 |
| ISBN |
9781119634430 electronic publication |
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1119634431 electronic publication |
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9781119634409 adobe electronic book |
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1119634407 adobe electronic book |
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9781119634461 electronic book |
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1119634466 electronic book |
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hardcover |
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