- Popular R articles this week are: colormap by Dan Kelley (Professor of Oceanography at Dalhousie University), The new look of learning R by DataCamp, Writing an R package from scratch by Hilary Parker (Data Analyst at Etsy), Test coverage of the 10 most downloaded R packages by Quartz Bio, How to Code Something ‘New’ in R by Francis Smart (PhD student at Michigan State University) and Reading large data tables in R by Fabio Marroni.
- If you roll a fair die 6 times, what is the probability that there is at least one pair of identical consecutive face values?
- Great news! The RSS is setting a data analysis challenge this year. The top three teams will be invited to present their results in a special session at the RSS Annual Conference in September 2014, and submissions will be considered for publication in the Journal of the Royal Statistical Society, Series C. If you are interested, here are the details.
- And finally, do you fly frequently? If so, you may want to know how to Automatically Scrape Flight Ticket Data Using R and Phantomjs.
- Two pieces of interesting data visualization work attracted some attention this week. How Americans Die by Matthew Klein of Bloomberg Visual Data and The Music America’s Listening To by Chris Kolmar of Movoto Blog.
- Popular R articles of the week are: Testing for Linear Separability with Linear Programming in R by Raffael Vogler, Twitter Extraction by Ethan Fosse, Simpson’s Paradox Is Back by Mad (Data) Scientist, and Object Oriented Programming with R: An example with a Cournot duopoly by Bruno Rodrigues.
- Have you ever tried Julia or have considered adopting it? Econometrics by Simulation reviews Julia from an R user’s perspective for those who are interested in learning this programming language.
- Rapport summarizes some key metrics about the popularity of R like the number of R Foundation members per country all over the world, and presents his findings in a report called R activity around the world.
- And finally, Why are R users so damn Stingy?!
- Do you know anything about the Hilbert Matrix (other than it is probably named after David Hilbert)? In his post this week, Nicholas Horton, Professor of Statistics at Amherst College, explains what it is, and how to create these matrices using both SAS and R.
- Xi’an discusses a new paper by Randal Douc, Florian Maire, and Jimmy Olsson called MCMC for sampling from mixture models.
- Some popular statistical articles this week are: Modeling Data With Functional Programming In R by Cartesian Faith, Make your ggplots shareable, collaborative, and with D3 by Matt Sundquist, Implementing a Principal Component Analysis (PCA) by Sebastian Raschka (for Python), and Ordering Datasets Alphabetically by geomorph.
- And finally, have you ever tried the popular mobile game 2048? If not, here are some code that you can run on your machine and start playing the game with R.
- R 3.1.0 (codename “Spring Dance“) is released this week!
- Do you invest in the stock market? If so, you may know the so-called 60/40 rule (invest 40% in bonds and 60% in stocks). But do you really believe this strategy? Eran Raviv performs some simulation studies and tries to verify whether the 60/40 rule is a wise choice or simply a myth.
- Popular R articles of the week: “Pretty” table columns and Calculating confidence intervals for proportions by Alan Haynes (Insights of a PhD student), Interpreting interaction coefficient in R by Lionel H. (biologyforfun) and Extract CSV data from PDF files with Tabula by Nathan Yau (Flowingdata).
- And finally, the most loyal fans in the NBA are…
- To give this year’s April Fools’ day a more analytical touch, here are The 7 Funniest Data Cartoons.
- Xi’an discusses a new paper by Scott Schmidler and his Ph.D. student Douglas VanDerwerken called Parallel MCMC.
- Tim Harford of Financial Times shares his thoughts on Big Data in an article called Big data: are we making a big mistake?
- David Springate publishes three very useful R articles this week: Develop in RStudio, run in RScript, Functional programming in R, and Two R tutorials for beginners.
- And finally, Revolution Analytics summarizes some recent news and reports on how the rise of the “R” computer language brings open source to science.