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Statistical Computing: An Introduction to Data Analysis using S-Plus

For anything more, you are probably going to need to see a statistician anyway. The book's website includes 3 additional chapters on gamma errors, additive models, and multivariate statistics. I use this book in two ways: In case after case, Crawley goes out of his way to show how and why statistical tests are calculated the way they are. S is ideally suited for this, since it makes the math painless and hides it behind nice graphical output, and lets you concentrate on understanding the concepts. If you are a student or professional who uses statistics and R or S-Plus, I can't recommend it highly enough, especially if you are someone who doesn't naturally think in mathematical symbols, or if you are more interested in learning how to do something and in understanding why it works, than in reading proofs or doing the underlying algebra.

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The Basics of S-PLUS

It is geared towards those who will be using the command line interface. Professor Ripley holds the Chair of Applied Statistics at the University of Oxford, and is the author of four other books on spatial statistics, simulation, pattern recognition and neural networks. Readers are assumed to have a basic grounding in statistics, and so the book is intended for would-be users of S-PLUS and both students and researchers using statistics. As a researcher and introductory behavioral statistics teacher this book has proven invaluable to me.

Crawley explains the connecting ideas that foster understanding that so many others seem to omit. Teaching statistics graphically rather than formulaically using the free student version of s-plus, my students come away understanding the foundations of statistics including measures of central tendency, probability distributions, regression, and ANOVA.

The interesting thing is that when I need an introduction to survival analysis or non-linear regression, I'm able to pick up the same book. The companion volume on S programming will provide an in-depth guide for those writing software in the S language.


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The authors have written several software libraries which enhance S-PLUS ; these and all the data sets used are available on the Internet in versions for Windows and Unix. There are extensive on-line complements covering advanced material, user-contributed extensions, further exercises and new features of S-PLUS as they are introduced.


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  • Some additional exercises on both S programming and data analysis are available for downloading. There are answers to almost all the programming exercises and some of the data analysis problems. The PDF version has extensive hyperlinks, for example between exercises and their answers.


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    • This book explains the basics of S-PLUS in a clear style at a level suitable for people with little computing or statistical knowledge. Each chapter also includes a collection of exercises which are accompanied by fully worked-out solutions and detailed comments.

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      Open Preview See a Problem? Thanks for telling us about the problem. Return to Book Page. Preview — Statistical Computing by Michael J. Many statistical modelling and data analysis techniques can bedifficult to grasp and apply, and it is often necessary to usecomputer software to aid the implementation of large data sets andto obtain useful results.

      S-Plus is recognised as one of the mostpowerful and flexible statistical software packages, and it enablesthe user to apply a number of statistical methods, ra Many statistical modelling and data analysis techniques can bedifficult to grasp and apply, and it is often necessary to usecomputer software to aid the implementation of large data sets andto obtain useful results.

      S-Plus / R

      S-Plus is recognised as one of the mostpowerful and flexible statistical software packages, and it enablesthe user to apply a number of statistical methods, ranging fromsimple regression to time series or multivariate analysis. Thistext offers extensive coverage of many basic and more advancedstatistical methods, concentrating on graphical inspection, andfeatures step-by-step instructions to help the non-statistician tounderstand fully the methodology.

      Hardcover , pages. Published May 22nd by Wiley first published April 9th To see what your friends thought of this book, please sign up. To ask other readers questions about Statistical Computing , please sign up. Be the first to ask a question about Statistical Computing.

      Modern Applied Statistics with S-PLUS. Third Edition

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