2011 | ISBN: 1849512086 | PDF | 300 pages | 7 Mb

This is a practical, step by step guide that will help you to quickly become proficient in the data analysis using R. The book is packed with clear examples, screenshots, and code to carry on your data analysis without any hurdle. If you are a data analyst, business or information technology professional, student, educator, researcher, or anyone else who wants to learn to analyze the data effectively then this book is for you. No prior experience with R is necessary. Knowledge of other programming languages, software packages, or statistics may be helpful, but is not required.

English | 2010 | ISBN: 0123751047 | 336 pages | PDF | 3,5 MB

Designed for a one or two semester senior undergraduate or graduate bioinformatics course, Statistical Bioinformatics takes a broad view of the subject - not just gene expression and sequence analysis, but a careful balance of statistical theory in the context of bioinformatics applications.

English | 2013 | ISBN-10: 3110307286 | 359 pages | PDF | 4,5 MB

This book is the revised and extended second edition of Statistics for Linguistics with R. The comprehensive revision includes new small sections on programming topics that facilitate statistical analysis, the addition of a variety of statistical functions readers can apply to their own data, and a revision of overview sections on statistical tests and regression modeling.

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**Gopal K Kanji, "100 Statistical Tests"**

Sage Publications Ltd | ISBN: 141292376X | Third Edition | PDF | 256 pages | 1.2 MB

Sage Publications Ltd | ISBN: 141292376X | Third Edition | PDF | 256 pages | 1.2 MB

This expanded and updated Third Edition of Gopal K. Kanji’s best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. Each entry begins with a short summary statement about the test’s purpose, and contains details of the test objective, the limitations (or assumptions) involved, a brief outline of the method, a worked example, and the numerical calculation.

English | 2006-02-17 | ISBN: 1584885394 | 269 pages | PDF | 1,4 mb

R is dynamic, to say the least. More precisely, it is organic, with new functionality and add-on packages appearing constantly. And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields.