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R in Action Data Analysis and Graphics with R Robert ~ R in Action Data Analysis and Graphics with R Robert Kabacoff on FREE shipping on qualifying offers Summary R in Action Second Edition presents both the R language and the examples that make it so useful for business developers Focusing on practical solutions

SAS and R Data Management Statistical Analysis and ~ An UptoDate AllinOne Resource for Using SAS and R to Perform Frequent Tasks The first edition of this popular guide provided a path between SAS and R using an easytounderstand dictionarylike approach

objects in R via R in Action Rstatistics ~ For readers of this blog there is a 38 discount off the “R in Action” book as well as all other eBooks pBooks and MEAPs at Manning publishing house simply by using the code rblogg38 when reaching checkout

R Bioconductor Manuals ~ This R tutorial provides a condensed introduction into the usage of the R environment and its utilities for general data analysis and clustering

Awesome R Find Great R Packages ~ Awesome R A curated list of awesome R packages and tools Inspired by awesomemachinelearning For better navigation see

An Introduction to R ~ This is an introduction to R “GNU S” a language and environment for statistical computing and graphics R is similar to the awardwinning 1 S system which was developed at Bell Laboratories by John Chambers et al It provides a wide variety of statistical and graphical techniques linear and

Post hoc analysis for Friedmans Test R code R ~ My goal in this post is to give an overview of Friedman’s Test and then offer R code to perform post hoc analysis on Friedman’s Test results

LeaRning Path on R – Step by Step Guide to Learn Data ~ Learning path on R provides a step by step guide to become a data scientist using R The path includes exercises tutorials best practices

R Data ImportExport ~ 11 Imports The easiest form of data to import into R is a simple text file and this will often be acceptable for problems of small or medium scale

Rbloggers tutorials for learning R ~ R packages are the fuel that drive the growth and popularity of R R packages are bundles of code data documentation and tests that are easy to share with others


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