- Alvaro Galindo reviews Social Media Mining with R by by Nathan Danneman and Richard Heinmann.
- Some popular articles on R tip and tricks are: R has some sharp corners by Win-Vector LLC, Sample uniformly within a fixed radius by Forester (Assistant Professor at the University of Minnesota Twin Cities), The Birthday Simulation by Wes Stevenson, and didYouMean() Function: Using Google to correct errors in Strings by Sam Weiss.
- R bloggers compiles a list of R related positions for those who are on the job market.
- Xi’an discusses a special issue Statistical Science named Big Bayes Stories: A Collection of Vignettes.
- Last week, we featured an article on R vs. Julia. This week, Matloff (aka Mad (Data) Scientist) writes another comparison called R beats Python! R beats Julia! Anyone else wanna challenge R?
- Are you a self-taught “scientist programmer”? Here is why people think code written by people like you is ugly.
- As always, R articles are extremely popular. This week, we have: Facebook teaches you exploratory data analysis with R by Revolution Analytics, Beyond R, or on the Hunt for New Tools by Quintuitive, Bootstrap Critisim (with example) by Eran Raviv, The apply command 101 by Learning R by Imitation, and Can We do Better than R-squared? by Learning as You Go.
- Julia is a new programming language (only 2 years old) for scientific computing and it has gained lots of popularity recently. In the past, we shared some articles comparing R and Julia. This week, Alvaro Galindo writes another comparison called Julia versus R – Playing around.
- Sébastien Bubeck, assistant professor at Princeton, releases the first draft of his monograph based some old lecture notes called Theory of Convex Optimization for Machine Learning.
- And finally, happy Victoria Day to those in Canada!
- Looking for a job? Here are some jobs compiled by R-bloggers that may be of interest to you.
- Homer White, professor of mathematics at Georgetown College, shares his Five Reasons to Teach Elementary Statistics With R.
- Seven R Quirks That Will Drive You Nutty.
- Some popular R articles this week are: how to build a sales dashboard with R, Optimising your R code, and Modelling seasonal data with GAMs.
- And finally, Xi’an discusses bridging the gap between machine learning and statistics.
- 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?!