**http://www.ats.ucla.edu/stat/r/**

Reshape R provides a variety of methods for reshaping data prior to analysis. Transpose Use the t() function to transpose a matrix or a data frame. Exploratory Data Analysis and Regression in R Exploratory Data Analysis (EDA) and Regression This tutorial demonstrates some of the capabilities of R for exploring relationships among two (or more) quantitative variables. Bivariate exploratory data analysis We begin by loading the Hipparcos dataset used in the descriptive statistics tutorial, found at Type hip <- read.table(" header=T,fill=T) names(hip) attach(hip) In the descriptive statistics tutorial, we considered boxplots, a one-dimensional plotting technique.

R Tutorial — R Tutorial 321a Boyd Graduate Studies University of Georgia Athens, Georgia 30602 Introductory Materials¶ These materials are designed to offer an introduction to the use of R. R: The R Datasets Package Documentation for package ‘datasets’ version 3.3.0 DESCRIPTION file. Help Pages R Starter Kit R Starter Kit This page is intended for people who: These materials have been collected from various places on our website and have been ordered so that you can, in step-by-step fashion, develop the skills needed to conduct common analyses in R. Statistics with R Warning Here are the notes I took while discovering and using the statistical environment R. However, I do not claim any competence in the domains I tackle: I hope you will find those notes useful, but keep you eyes open -- errors and bad advice are still lurking in those pages... Should you want it, I have prepared a quick-and-dirty PDF version of this document.

heather.cs.ucdavis.edu/~matloff/r.html Professor Norm Matloff Dept. of Computer Science University of California at Davis Davis, CA 95616 R is a wonderful programming language for statistics and data management, used widely in industry, business, government, medicine and so on. And it's free, an open source product. The S language, of which R is essentially an open source version, won the ACM Software System Award in 1998. Installing and Starting SparkR Locally on Windows OS and RStudio Introduction With the release of Apache Spark 1.4.1 on July 15th, 2015, I wanted to write a step-by-step guide to help new users get up and running with SparkR locally on a Windows machine using command shell and RStudio. SparkR provides an R frontend to Apache Spark and using Spark’s distributed computation engine allows R-Users to run large scale data analysis from the R shell.

R Programming Welcome to the R programming Wikibook This book is designed to be a practical guide to the R programming language[1]. R is free software designed for statistical computing. There is already great documentation for the standard R packages on the Comprehensive R Archive Network (CRAN)[2] and many resources in specialized books, forums such as Stackoverflow[3] and personal blogs[4], but all of these resources are scattered and therefore difficult to find and to compare. The aim of this Wikibook is to be the place where anyone can share his or her knowledge and tricks on R. It is supposed to be organized by task but not by discipline[5].

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