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Binding: PaperbackDewey Decimal Number: 519 EAN: 9780387790534 Edition: 2nd ISBN: 0387790535 Label: Springer Manufacturer: Springer Number Of Items: 1 Number Of Pages: 364 Publication Date: August 15, 2008 Publisher: Springer Studio: Springer Editorial Review: Product Description: 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. Average Rating:
 Rating:  - Intro. stats with RThis book seems like an excellent reference if you read though it in order and follow along using the example dataset provided online. However, I find that the transition to using my own data is far from clear. The book does not prepare you very well for using your own data, and barely discusses any type of matrices. This book if for univariate analysis, and univariate data. As a reference it is definitely not as well suited. Looking up a topic in the index and jumping to that page often drops ... Read More Rating:  - Good book on how to use R for basic statistical analysisIf you are new to statistics or have a limited knowledge of basic programming skills this book is not for you. If you understand basic statistics and know something about programming then this is an excellent introduction to how to use R to perform basic statistical analysis. It is not an R manual, as was stated in the preface. Nor is it an introductory statistics book by itself. It describes the analysis technique in high level, walks through the analysis step by step, and shows you how to use R ... Read More Rating:  - Fast shipping, good quality. Thanks!The shipping is fast and the book arrived in good quality. I appreciate it very much. Thanks! Rating: - Excellent resourceI bought this book a little over a year ago when a friend and colleague insisted I learn the R system for our collaborative work. I am not a professional statistician, but an engineer and researcher who needs and uses statistics in the course of my professional work. I found this book approachable and informative from the non-professional perspective. (That is, from the viewpoint of a non-statistician.) I found enough examples to guide me through the process of bringing my datasets into the ... Read More Rating: - Great for learning the languageIf you have learned the stat concepts behind these procedures already, this is book is great. I think this book is very helpful for people who have had a few stat courses where the professor used a competing stat software package. I really like how the author repeats some of the important syntax explanations throughout the book (for example, why attaching a data frame makes the syntax more concise). This approach makes it better than trying to learn R from the isolated html help files. |
