S Is A Powerful Environment For The Statistical And Graphical Analysis Of Data It Provides The Tools To Implement Many Statistical Ideas That Have Been Made Possible By The Widespread Availability Of Workstations Having Good Graphics And Computational Capabilities This Book Is A Guide To Using S Environments To Perform Statistical Analyses And Provides Both An Introduction To The Use Of S And A Course In Modern Statistical Methods Implementations Of S Are Available Commercially In S PLUS R Workstations And As The Open Source R For A Wide Range Of Computer Systems The Aim Of This Book Is To Show How To Use S As A Powerful And Graphical Data Analysis System Readers Are Assumed To Have A Basic Grounding In Statistics, And So The Book Is Intended For Would Be Users Of S PLUS Or R And Both Students And Researchers Using Statistics Throughout, The Emphasis Is On Presenting Practical Problems And Full Analyses Of Real Data Sets Many Of The Methods Discussed Are State Of The Art Approaches To Topics Such As Linear, Nonlinear And Smooth Regression Models, Tree Based Methods, Multivariate Analysis, Pattern Recognition, Survival Analysis, Time Series And Spatial Statistics Throughout Modern Techniques Such As Robust Methods, Non Parametric Smoothing And Bootstrapping Are Used Where Appropriate This Fourth Edition Is Intended For Users Of S PLUS 6.0 Or R 1.5.0 Or Later A Substantial Change From The Third Edition Is Updating For The Current Versions Of S PLUS And Adding Coverage Of R The Introductory Material Has Been Rewritten To Emphasis The Import, Export And Manipulation Of Data Increased Computational Power Allows Even Computer Intensive Methods To Be Used, And Methods Such As GLMMs, MARS, SOM And Support Vector Machines Are Considered.

William Venables

Hardcover

498 pages

Modern Applied Statistics with S (4th Edition)

W.N. Venables

English

23 July 2017

W.N. Venables

9780387954578

W.N. Venables

10 thoughts on “Modern Applied Statistics with S (4th Edition)”

This is an very good resource for learning how to implement various statistical methods in R which is based on S The authors do provide some theoretical and mathematical explanation of the various methods they cover, which was helpful as a refresher, but I found it was not as effective for learning the basis of methods I didn t already know, especially because the authors go through things rather quickly They have a wealth of examples from a wide range of fields, which is helpful for people coming to the book from different disciplines However, I found that, once they produced statistical results for a given example, they didn t explain what those results would mean, even in cases in which they had gone into a fair bit of detail explaining the statistical questions they were analyzing the data to ask Since this isn t a statistics textbook as I said before , this is fair, but it woul...

First, I want to say If you don t know it yet , this book even is not recent, is absolutely a basic manual for R, so don t let yourself be distracted by the title There are lots of R functions that will lead you in it s references to this book, and this text is pure gold Venables and Ripley are not only making easy to copy and paste scripts, but they are also giving great introductions, c...

I think this was the first book I bought on R, and it s certainly the most well thumbed The graphing examples are really quite good, but it s a really hard slog if you re new to R Once you ve gotten familiar, though, check it out if you re doing a lot of data visualization work.

This is an very good resource for learning how to implement various statistical methods in R which is based on S The authors do provide some theoretical and mathematical explanation of the various methods they cover, which was helpful as a refresher, but I found it was not as effective for learning the basis of methods I didn t already know, especially because the authors go through things rather quickly They have a wealth of examples from a wide range of fields, which is helpful for people coming to the book from different disciplines However, I found that, once they produced statistical results for a given example, they didn t explain what those results would mean, even in cases in which they had gone into a fair bit of detail explaining the statistical questions they were analyzing the data to ask Since this isn t a statistics textbook as I said before , this is fair, but it woul...

First, I want to say If you don t know it yet , this book even is not recent, is absolutely a basic manual for R, so don t let yourself be distracted by the title There are lots of R functions that will lead you in it s references to this book, and this text is pure gold Venables and Ripley are not only making easy to copy and paste scripts, but they are also giving great introductions, c...

I think this was the first book I bought on R, and it s certainly the most well thumbed The graphing examples are really quite good, but it s a really hard slog if you re new to R Once you ve gotten familiar, though, check it out if you re doing a lot of data visualization work.