I have been working on developing some interactive tools for demonstrating statistical principles. The advent of the shiny framework for R from the RStudio team has made this very easy to do. These demos are still in the development...

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R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. One of my main motivations to install R is Sweave. The Sweave is a literate programming language which integrates LaTeX and R code. The main idea of the Sweave is to combine data analysis code...

At the time of the creation of this blog, Cronbach’s 1951 piece on coefficient alpha has 18,132 citations according to google scholar. The main use of coefficient alpha is to assess internal consistency reliability of a test or survey. Although it may have been forgotten, the proof Cronbach demonstrated established that coefficient alpha is the mean of all split...

Here’s a sneak peak into upcoming visualisation work. I’ve been working a bit on MDS (Multi-dimensional scaling), a classical technique for visualising distance data. Classical MDS is useful, but interactive MDS is *much* more useful. Using D3, a Javascript visualisation framework, it’s relatively easy to make interactive MDS plots. This example shows how basic interaction

This a brief guide to using R in collaborative, social ways. R is a powerful open-source programming language for data analysis, statistics, and visualization, but much of its power derives from a large, engaged community of users. This is an introduction to tools for engaging the community to improve your R code and collaborate with others. (Am I...

For the introductory statistic student confidence intervals can seem a daunting concept to grasp. Quite simply put it is an interval that we have a certain measure of confidence that the population parameter falls into. The 95% confidence is the most common value chosen in my academic circle. Nevertheless, many others may be viable as well as long as...

In a previous post I reviewed my interactions with Python the programming language and the community following the New Years’ Python Meme that’s making the rounds on Twitter and the like. And now, I’m shamelessly stealing it to look at how I used R in 2012. I figure I should probably let the #2012pythonmeme stay Python-only,

In his recent post 100 most read R posts for 2012 (stats from R-bloggers) – big data, visualization, data manipulation, and other languages Tal Galili - the guy behind R-Bloggers - presents his wishlist for 2013. Among other things he states &ldquo...