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Statistics: an introduction using R Michael J. Crawley
Publisher: Wiley

It introduces tools to These quantitative tools are implemented using the free, open source software program R. This is a twelve-day intensive course (6 hr/day), with additional Suggested statistics references for review are listed below. This book provides an introduction, suitable for advanced undergraduates and beginning graduate students, to two important aspects of molecular biology and biophysics: computer simulation and data analysis. You'll learn how to wri I have bought R in a Nutshell some time ago (1-st edition) and I was pleased with it. An attempt to make sense of econometrics, statistics, applied analytics, biometrics, data mining, machine learning, experimental design, bioinformatics, . The primary aim of the course is to learn methods in R for: 1) data manipulation 2) exploratory data analysis, 3) data analysis using standard statistical methods, and 4) graphical presentation of data and results. Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. I am using R casually for doing server logs analysis, mostly. Foundations and Applications of Statistics: An Introduction Using R (Pure and Applied Undergraduate Texts): Randall Pruim: 9780821852330 Description. To get started with R, I'd recommend the freely available textbook Introduction to Probability and Statistics Using R (IPSUR [PDF]). In Chapter 5 of Using R for Introductory Statistics we get a brief introduction to probability and, as part of that, a few common probability distributions. If you're considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. R provides an excellent environment for general numerical and statistical computing and graphics, with capabilities similar to Matlab®. I thought that R in a Nutshell would introduce them to concepts about R programming (S3 objects for example), without clouding the issue with statistical topics. More advanced methods (generalized liner models, time series, and bioinformatics) will also be introduced using specific examples. Introduction to Probability and Statistics Using R. An Introduction to Social Network Analysis with R and NetDraw. To introduce the ideas and methods of statistical modelling and statistical model exploration. However, their statistical knowledge is almost non-existent. It is very decent introduction to R.