I - RapidAnalytics. Collaboration is key with RapidMiner Server.

Shared repositories allow you to work with coworkers and contributors throughout your organization and beyond, using interactive dashboards you build to meet your specific needs. Assign specific tasks, pool your resources, and share information with everyone in your team at once, from anywhere in the world. We make it easy to access, monitor, and share your analysis anywhere, anytime. Ideas, issues, knowledge, data - visualized! Getting-started:what-is-r:what-is-r. The description on the main R web page is good, and needn’t be repeated here; it describes a bit about R’s history and technical capabilities.

Some things you might want to know about R if you’re encountering it for the first time: R is (according to the description linked above) “a language and environment for statistical computing and graphics”; you can think of it as a combination of a statistics package and a programming language. R is completely free; you don’t have to pay for it, and you can make any modifications you want to it R runs on Windows, MacOS, Linux, and many Unix variants R is not supported by any commercial enterprise, but it has a very active development community, and there are companies that offer training courses etc.. Clustergram: A graph for visualizing cluster analyses (R code) 150+ R Abbreviations. The R programming language includes many abbreviations.

Abbreviations exist in function names, argument names, and allowed values for arguments. This post expands on over 150 R abbreviations with the aim of making it easier for users new to R who are trying to memorise R commands. Context Abbreviations save time when typing and can make for less cumbersome code.

However, abbreviations often make it more difficult to remember a command. R has been developed by a group of technical experts with backgrounds in Linux and Unix, mathematics, statistics, and statistical computing. Start [R-Node] Writing /var/www/r-node/data/cache/2/2d54f1d82cf67432cd4c82a000527112.i failed Unable to save cache file. Hint: disk full; file permissions; safe_mode setting. Writing /var/www/r-node/data/cache/2/2d54f1d82cf67432cd4c82a000527112.xhtml failed R-Node is a web front-end to the statistical analysis package R .

R-Node. Friday, March 7 2014 Saturday, October 19 2013 Saturday, August 10 2013 Thursday, August 1 2013 Saturday, July 13 2013 Thursday, March 28 2013 Wednesday, March 20 2013 Saturday, February 9 2013.

Yeroon.net/ggplot2. Introduction yeroon.net/ggplot2 is a web interface for Hadley Wickham's R package ggplot2.

A Practical Guide to Geostatistical Mapping. R-statistics blog. Ggplot. had.co.nz. Statistics. Stunning Infographics and Data Visualization. Feb 02 2010 Information graphics, or infographics, are visual representations of information, data or knowledge.

The graphics are used where complex information needs to be explained quickly and clearly, such as on signs and maps and in journalism, technical writing and education. Today, infographics surround us in the media, in published works both mainstream and scientific and in road signs and manuals. They illustrate information that would be unwieldy in text form and act as a visual shorthand for everyday concepts, such as “Stop” and “Go.” Creating an effective infographic requires both artistic sense and a clear vision of what to tell the audience. You may be interested in the following related posts: Beautiful Infographics And Data Visualization. Incanter: Statistical Computing and Graphics Environment for Clojure. CRC Press Online - Book: Introduction to Scientific Programming and Simulation Using R.

Features Examines R as the medium for scientific computation Demonstrates simple mathematical tools in the context of stochastic modeling Introduces simple yet useful mathematical tools in the context of stochastic modeling.

CRC Press Online - Book: A Handbook of Statistical Analyses Using R, Second Edition. Features Shows how to obtain informative graphical output using R Provides R code so readers can perform their own analyses Emphasizes the practical application and interpretation of results rather than focusing on the theory behind the analyses.

Talks. R and Big Data Invited Panel Presentation, Big Data Summit, Research Park, University of Illinois at Urbana-Champaign.

Champaign, IL, December 6, 2013 Pdf version of presentation slides Seamless R and C++ Integration with Rcpp: Introduction and Examples Invited Colloqium, Center for Research Methods and Data Analysis, University of Kansas, Lawrence, KS, November 16, 2013 Pdf version of presentation slides part 1: Rcpp Intro, part 2: RcppArmadillo Examples, part 3: RcppZiggurat. A Data Analysis Framework.

The Free Statistics Calculators Website - Home. Welcome to version 3.0 of the Free Statistics Calculators website! These statistics calculators are free to be used by anyone in the research community at large. They are offered humbly in the hope that they will contribute in some small way to the advancement of science and the betterment of mankind. I hope you find them useful! The statistics calculators are organized into the 29 categories shown below. Clicking on a category name will display a list of calculators available for that category. Sample Size Calculator - Confidence Level, Confidence Interval, Sample Size, Population Size, Relevant Population - Creative Research Systems. This Sample Size Calculator is presented as a public service of Creative Research Systems survey software.

You can use it to determine how many people you need to interview in order to get results that reflect the target population as precisely as needed. You can also find the level of precision you have in an existing sample. Before using the sample size calculator, there are two terms that you need to know. These are: confidence interval and confidence level. If you are not familiar with these terms, click here.

Enter your choices in a calculator below to find the sample size you need or the confidence interval you have. Sample Size Calculator Terms: Confidence Interval & Confidence Level. Interactive Statistical Calculation Pages. SOFA Statistics Open For All - Home Page. IDE/Script Editors. Except for the MacOS and Windows versions of R frontends, no internal script editor is provided. The command 'options(editor = ...)' allows defining its own preferred external one. Several editors have been customized to enhance their functions regarding the edition of R scripts: S language syntax highlighting, execution of code directly from the editor, macro and templates,...

Here are some external editors with nice features for editing R scripts besides Emacs/ESS. Multiplatform solutions Komodo Edit is a powerful code editor for all kinds of source files and it runs an Linux, Windows and Mac OS X. Rpad - Google Code. PSPP. GNU PSPP is a program for statistical analysis of sampled data. It is a Free replacement for the proprietary program SPSS, and appears very similar to it with a few exceptions. The most important of these exceptions are, that there are no “time bombs”; your copy of PSPP will not “expire” or deliberately stop working in the future. Neither are there any artificial limits on the number of cases or variables which you can use. There are no additional packages to purchase in order to get “advanced” functions; all functionality that PSPP currently supports is in the core package.

PSPP is a stable and reliable application. A brief list of some of the PSPP's features follows below. Welcome. Homepage. Professor Rob J Hyndman. Dataplot. SOCR: Statistics Online Computational Resource. What are the main SOCR Components? The core SOCR educational and computational components include: Distributions (interactive graphs and calculators), Experiments (virtual computer-generated analogs of popular games and processes), Analyses (collection of common web-accessible tools for statistical data analysis), Games (interfaces and simulations to real-life processes), Modeler (tools for distribution, polynomial and spectral model-fitting and simulation), Graphs, Plots and Charts (comprehensive web-based tools for exploratory data analysis), Additional Tools (other statistical tools and resources), SOCR Wiki (collaborative Wiki resource), Educational Materials and Hands-on Activities (varieties of SOCR educational materials), SOCR Statistical Consulting and Statistical Computing Libraries.

How to use the SOCR Resources? SOCR: Statistics Online Computational Resource. R Commander. MacAnova Home Page. Resources to help you learn and use SPSS. [R-sig-teaching] R Equivalent of SPSS "Split File" and "AutoRecode" Introduction to Statistical Computing in R. A statistical package, such as SPSS or SAS, is primarily oriented toward combining instructions with rectangular case-by-variable datasets to produce (often voluminous) printouts. Such packages make routine data analysis relatively easy, but they make it relatively difficult to do things that are innovative or non-standard, or to add to the built-in capabilities of the package. In contrast, a good statistical computing environment also makes routine data analysis easy, but it additionally supports convenient programming; this means that users can extend the already impressive facilities of R.

An Introduction to R. Table of Contents. R: Statistical Software for Psychology Research. Crush-tools - Google Code. CRUSH (Custom Reporting Utilities for SHell) is a collection of tools for processing delimited-text data from the command line or in shell scripts. For help getting started using CRUSH, or to see a demo of what it can do, try the CrushTutorial. For a list of the utilities provided in CRUSH and links to their documentation, see the UserDocs.

Or see ApplicationDevelopmentWithCrush for a detailed look at writing applications using the CRUSH toolkit. Join the CRUSH discussion group at. Piwik - Web analytics - Open source. Free-SA. ★ 5.0 Stars (12) Ohloh Home Page. Scruffy Graphs for Ruby People. Website Optimizer - Adwords - Google. An Introduction to R - a tutorial for new users of R. About the Book This tutorial manual provides a comprehensive introduction to GNU R, a free software package for statistical computing and graphics.

The R Users Group at University of Arizona.