I write about R every weekday at the Revolutions blog: ?blog.revolutionanalytics.com and every month I post a summary of articles from the previous month of particular interest to readers of r-help. In case you missed them, here are some articles related to R from the month of September: The deadline to enter the "R Applications" contest with $20,000 in prizes is October 31: bit.ly/qufEjy The RHadoop Project, a new collection of open-source R packages from Revolution Analytics, makes it possible to write map-reduce jobs in R to analyze huge data sets stored in Hadoop: bit.ly/nbG3qv . The slides and replay from a webinar on this project are available for download: bit.ly/offYSJ Instructions on how to read Google Spreadsheets into R have been updated to work with Googe's SSL connection: bit.ly/nYuSeD Insurance giant Lloyds of London uses R for performance management, exposure analysis, Monte-Carlo simulation, data visualization, reporting, and much more: bit.ly/oqlu4k A summary of discussions on LinkedIn comparing R and SAS for businesses: bit.ly/oWKdtP A KDnuggets poll finds R to be the most commonly-used software for data mining and analytics: bit.ly/r4aHqo Fortune magazine declares "Data Scientist" to be the "hot new gig in Tech": bit.ly/q7ZNCu Two presentations from Revolution Analytics on analyzing big data with R: bit.ly/r5VbGR A ggplot2 chart created with R is used to illustrate the "half-life" of links posted to Facebook, YouTube and Twitter, based on data from bitly: bit.ly/pBqokB I published an article on ReadWriteWeb, "Unlocking Big Data with R", with examples from the New York Times, Orbitz and OkCupid: bit.ly/mWqqgR A review of The Economist's feature article on how incorrect analysis and failures in reproducible research (detected partly using R) led to a cancer trial being shut down: bit.ly/oRUpVs An example from Dirk Eddelbuettel on using RCpp to speed up recursive algorithms in R: bit.ly/nq4NdH Revolution Analytics is running weekly webinars: upcoming topics include uses of R with SAS in Banking, Revolution R Enterprise, and Scalable Data analysis in R: bit.ly/nVo432 How to create time series in R from very large time-stamped log files: bit.ly/phOf3H A preview of R 2.14.0, to be released on October 31: bit.ly/mVsg69 . R 2.13.2 was released on September 29: bit.ly/mRKVux The 2010 "Flash Crash" was the largest one-day stock market decline in history. An analysis in R of 24 billion trades investigates whether SEC rules to prevent a reoccurrence are effective: bit.ly/ohOv12 Nathan Yau of FlowingData mentions R in a post about "5 misconceptions about data visualization", and I take issue with charts that inject a political point of view (and not to mention chartjunk) into data visualizations:?bit.ly/oaSQQh Revolution Analytics has partnered with Cloudera to support using R with Hadoop: bit.ly/oSKHh7 R user Harlan Harris created a presentation, "What is a Data Scientist, anyway", with a history of uses of the term: bit.ly/neWvU9 The R Graph Gallery has added social features, such as the ability to "like" a chart with Facebook: bit.ly/nnAB09 Other non-R-related stories in the past month included: more growth in analytics and data science jobs (bit.ly/r73Ijs), the fastest method for boarding airplanes (bit.ly/pKqxGB), conversations between chatbots (bit.ly/r29KRX), the strange images created by photographing propellers with iPhones (bit.ly/ovCF4D), an audible illusion (bit.ly/p0GR6X), and a visual trigonometric pun (bit.ly/qQLbB4). There are new R user groups (bit.ly/eC5YQe) in Tokyo, Shanghai, Stamford, Medford and Barcelona: bit.ly/ovwoYb . Meeting times for these groups can be found on the updated R Community Calendar at: bit.ly/bb3naW If you're looking for more articles about R, you can find summaries from previous months at blog.revolutionanalytics.com/roundups. Join the Revolution mailing list at revolutionanalytics.com/newsletter to be alerted to new articles on a monthly basis. As always, thanks for the comments and please keep sending suggestions to me at david at revolutionanalytics.com . Don't forget you can also follow the blog using an RSS reader like Google Reader, or by following me on Twitter (I'm @revodavid). Cheers, # David -- David M Smith <david at revolutionanalytics.com> VP of Marketing, Revolution Analytics? blog.revolutionanalytics.com Tel: +1 (650) 646-9523 (Palo Alto, CA, USA)