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Loading... Introductory Statistics with Rby Peter Dalgaard
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Wikipedia:Reference desk/Archives/Computing/2009 September 16 |
| Book description |
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R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. R is now in widespread use for teaching at many levels as well as for practical data analysis and methodological development.
This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. A supplementary R package can be downloaded and contains the data sets.
The statistical methodology includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one- and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last six chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, survival analysis, Poisson regression, and nonlinear regression.
In the second edition, the text and code have been updated to R version 2.6.2. The last two methodological chapters are new, as is a chapter on advanced data handling. The introductory chapter has been extended and reorganized as two chapters. Exercises have been revised and answers are now provided in an Appendix.
(retrieved from Amazon Fri, 24 Apr 2009 07:58:01 -0400)
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Runner up for Best Introductory Statistics book
Summary Review: This is the classic book introducing basic statistics using R, and it is still a great book for this purpose, exceeded only (in our opinion), by Statistics: An Introduction using R (2005) by Michael Crawley. (