It's not always easy getting the right size. The image is CC by Kristina Gill. A vital part of statistics is producing nice plots, an area where R is outstanding. The graphical ablility of R...

Add references and a style sheet Below I briefly outline why Pandoc is an essential part of my research workflow, and demonstrate how to seamlessly integrate it with a bibliographic system and code written in R to produce high quality word or pdf documents. I also...

(My colleague Jean-Louis Fouley, now at I3M, Montpellier, kindly agreed to write a review on the BUGS book for CHANCE. Here is the review, en avant-première! Watch out, it is fairly long and exhaustive! References will be available in the published version. The additions of book covers with BUGS in the title and of the corresponding

In this tutorial you will learn: what is a heatmap how to create a clean, highly customizable heatmap using heatmap.2 in the gplots package in R how to remove samples with poor output (not very many sequences) how to rearrange your samples by a metadata category how to make a color coded bar above the heatmap

Embarrassingly I'm stumped on this...I have a program in R for looking at grade distributions in my class. I found something weird recently with my 'ifelse' processing. I noticed that my program seemed to be over counting Cs and under counting...

The Cauchy distribution (?dcauchy in R) nails a flashlight over the number line and swings it at a constant speed from 9 o’clock down to 6 o’clock over to 3 o’clock. (Or the other direction, from 3→6→9.) Then counts Read more »

This guest post is by Tammer Kamel, Founder of Quandl Finding and formatting numerical data for analysis in R or Excel or indeed any application is a pain that all real world data analysts know all too well. In aggregate I have probably spent weeks of my life trying to find data on the web. And several more weeks...

I was flipping through my copy of William Cleveland’s The Elements of Graphing Data the other day; it’s a book worth revisiting. I’ve always liked Cleveland’s approach to visualization as statistical analysis. His quest to ground visualization principles in the context of human visual cognition (he called it “graphical perception”) generated useful advice for designing Related posts:

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