Here is the latest bag of tweets^*, which covers August 2015.

(*) These are interesting news that I found on Twitter and that I archive periodically.

• statsepi: BMI is a tool for epidemiological study of obesity - not individual assessment http://t.co/amdiANkI49 in light of http://t.co/GSUHMeHD0X (29 Aug)
• NadiehBremer: New Blog! How to create a #d3js flow chart with a circular twist - or hacking a Chord #dataviz http://t.co/vnOWBgWhCs http://t.co/1q3mPAevio (28 Aug)
• tomstafford: Does high citation count predict reproducibility? http://t.co/mS2nbB58Q6 quick supplementary analysis by me. tl;dr: not so much (28 Aug)
• BrianNosek: You can reproduce the entire #ReproducibilityProject yourself in R: https://t.co/AyE9TP41NW and follow the guide to analyses. #openscience (28 Aug)
• PhilGeek: Git being essential to my workflow has prevented me from text editing on iOS. Perhaps Working Copy is the way forward http://t.co/mFVYcxGE0O (28 Aug)
• statwonk: @timtriche @rdpeng @vsbuffalo I was pleasantly surprised with the distribution of clinical trials p-values, http://t.co/LI8vXuC9pC (28 Aug)
• freakonometrics: “Estimating the reproducibility of psychological science” http://t.co/TE1jq9z9I7 http://t.co/JIat9oIOg0 (28 Aug)
• b__k: This really is an awesome list of C tools: https://t.co/xCfqe6L2fS (28 Aug)
• FGRibreau: Postmaster Tools • analyze your email performance by @gmail http://t.co/mRLNyqzlXx (26 Aug)
• pomogajko: I actually do not enjoy Jupyter/Ipython. Especially for #datascience with #rstats background. Sorry. http://t.co/f08N5oL5Ck (24 Aug)
• KirkegaardEmil: Discretization and relative risk: an interactive visualization. http://t.co/NGp9AsyHZl #rstats #dataviz http://t.co/G4rXRf84DR (23 Aug)
• kinggary: Looking forward to seeing everyone at the FDA next week. Here are slides for my talk on matching http://t.co/hzVQO1v14D (21 Aug)
• YhatHQ: Gaussian Process School notes and ipython notebooks (gpss.cc) | http://t.co/lFQtmZdjs5 (21 Aug)
• stephensenn: #Statistics ‘How to test hypotheses if you must’ Interesting article by @AndrewPGrieve http://t.co/67YhWMSCmy (21 Aug)
• DrBunsen: GAM all the things. A nice overview (PDF): http://t.co/mBGGafshpC (19 Aug)
• YhatHQ: Producing Error Estimates with Residual Modeling | http://t.co/25MjYSPbNz (19 Aug)
• DiegoKuonen: MT @freakonometrics: Visualising theoretical distributions of #GLMs >http://t.co/tQMNfrPmCc by @MarkusGesmann #RStats http://t.co/knqxecZYKJ (18 Aug)
• mcmc_stan: If you’re looking for sparse variable selection, see @avehtari’s work. https://t.co/2Fbh9wmX3s (16 Aug)
• ericnovik: New Post: Getting Started with @mcmc_stan (using #rstats RStan interface) http://t.co/JG30pWfgoI (15 Aug)
• dataelixir: pandashells - Bringing the #python data stack to the shell prompt http://t.co/0iTWQBIOd7 #datascience (14 Aug)
• YhatHQ: One Trillion Edges: Graph Processing at Facebook-Scale (pdf) | http://t.co/tXa7fJkjRW (14 Aug)
• tdoyon: Data Exploration with Weight of Evidence and Information Value in #rstats http://t.co/woswME6yme (14 Aug)
• JanWillemTulp: anyone experience with Lightning-Viz ? http://t.co/uhZnSyfzTA (14 Aug)
• avehtari: Sparse variable selection using @mcmc_stan “Projection predictive variable selection using Stan+R” http://t.co/LLVOpdBWQ6 (14 Aug)
• KirkDBorne: [2 of 6] Periodic Table of #MachineLearning Libraries : http://t.co/jgCIAhIymf #BigData #DataScience http://t.co/2nCiLncuGL (13 Aug)
• TeXtip: How to make a graph of heteroskedasticity with TikZ/PGF? http://t.co/sOUuIAJIB9 http://t.co/Tetyu1jr1K (13 Aug)
• carlcarrie: EBook on Time Series Analysis https://t.co/NIreVt9PUL (11 Aug)
• SunitJain: #rstats : “rafalib package now on CRAN” http://t.co/SZgbGx6N2a (11 Aug)
• josefslerka: Text Processing in R http://t.co/qvlBeJI5VG #rstats (11 Aug)
• LouBajuk: Great overview of the state of interactive graphics in #rstats from @hadleywickham at #jsm2015 http://t.co/XLTnaJ6sYs (11 Aug)
• Gliese1214b: Glasseye: bringing together markdown, d3 and the Tufte layout #d3 #datavis #markdown #tufte http://t.co/hzoY1wWkJy… http://t.co/KRr9HZTg3q (10 Aug)
• m_a_upson: I wrote a blog post about #glmnet for regularisation in multiple linear regression #rstats #machinelearning… http://t.co/0bWFVwVeYi (10 Aug)
• ericcolson: Frequentism and Bayesianism V: Model Selection https://t.co/9mih8Y1zqH via @jakevdp (10 Aug)
• RevoAndrie: Package Rborist https://t.co/gAFPcSj3mD is a fast, extensible implementation of random forest algorithm in #rstats #jsm2015 (10 Aug)
• RevoAndrie: For multinomial logistic regression in #rstats, use package ClusterBootMultinom at https://t.co/Wx12pJoeAA #jsm2015 (10 Aug)
• RevoAndrie: The rctrack package can help with reproducibility of your #rstats results http://t.co/zWRRC7wqEx #jsm2015 (10 Aug)
• JuliaGustavsen: ggtree looks useful: nice viz and annotations of phylogenetic trees with ggplot #rstats http://t.co/lbNKw3qIDI thanks @guangchuangyu (10 Aug)
• rasbt: Awesome work: The curated list of “data science blogs” turned into a blog aggregator: http://t.co/xzKWgCykkV http://t.co/9tevL2XobU (10 Aug)
• jakevdp: The early release of my @OReillyMedia book is out! http://t.co/fAh6eHFa0S The cover is a Mexican Bearded Lizard. :) http://t.co/IobT3jdZGt (9 Aug)
• ScienceHA: Architecture of a Data Visualization: http://t.co/xyaAPlUMwh Inform, Entertain & Engage! @giorgialupi @accuratstudio http://t.co/q5B2QLhfho (8 Aug)
• BigDataGal: #rstats #datascience Matrix Factorization Comes in Many Flavors: Components, Clusters, Building Blocks and Ideals http://t.co/1Vmk4bx8IX (8 Aug)
• DiegoKuonen: MT @askdrstats: Combating anti-statistical thinking w/simulation-based and #bootstrap methods in undergrad curriculum http://t.co/KuKwmpDJS4 (8 Aug)
• brianrahmer: Understanding Statistical Power and Significance Testing: an interactive visualization… http://t.co/KERCE6BIQb (8 Aug)
• trebor74hr: Working with maps in #Python #gis http://t.co/wlFv5aAj9v (8 Aug)
• romunov: Another free javascript book. http://t.co/K8nUMTPuFy (8 Aug)
• LispDaily: Another excellent Common #Lisp blog post / tutorial http://t.co/ZgZ3zEsEBN #lisp #commonlisp (7 Aug)
• noamross: Oh wow, this gallery of plots by @nbrgraphs, maintained by @JennyBryan, is GREAT. http://t.co/XTqrIM9oex (7 Aug)
• KirkDBorne: Interactive #DataViz for the Web (Free Online Book) http://t.co/iaa1nv695k #abdsc #BigData #DataScience http://t.co/ObU9ktJDLn (6 Aug)
• rgaiacs: If you are going to teach #Python, #Git, #shell or #HTML5 you should read @remiemonet’s blog post http://t.co/iPDk5eLmi9 @swcarpentry (6 Aug)
• genetics_blog: gene.iobio: find disease-causing genetic variants http://t.co/diq7K6Wcuw http://t.co/8c0PZ6tl3l (6 Aug)
• kwbroman: Slides for my talk at #JSM2015 on interactive graphics with #d3js & #rstats http://t.co/iCoHtXvsOk http://t.co/yoOXcbp6rK (6 Aug)
• YhatHQ: Introduction to Computer Science and Programming Using #Python | edX | http://t.co/EQLobc9ced (6 Aug)
• tingenek: Rather fine css from @daveliepmann brings #Tufte handout styling to your site. https://t.co/FUxt5xWYfd (5 Aug)
• davdittrich: Survival Analysis http://t.co/UUbgqiIayc #rstats (5 Aug)
• mikelove: trying out: alias rhelp=“Rscript -e ‘args <- commandArgs(TRUE); help(args[2], package=args[3], help_type="html"); Sys.sleep(5)’ –args” (5 Aug)
• kwbroman: Tutorial on organizing data in spreadsheets. http://t.co/ArqjkMAKtN (5 Aug)
• trebor74hr: #Postgres Guide http://t.co/E06fgHwjyd (3 Aug)
• ze3t: Nice tool! Fire up your toolchain when files change: http://t.co/QexnfCwCLT & https://t.co/TTLxoO1zhk (2 Aug)
• rasbt: “8 Tools That Show What’s on the Horizon for the Python Data Ecosystem” 3 new & useful tools for I didn’t know about http://t.co/oGMxYQjgtD (2 Aug)
• eddelbuettel: And another nice CRAN addition: Large-scale distributed gradient boosting from https://t.co/qqdUBe8XIO https://t.co/SHMbAASIL9 (1 Aug)
• rasbt: Whoa, finally!!! “Pandas Releasing the GIL” (or: #Python pandas gets multihreading, yeah!) http://t.co/cVReRMT3u0 (1 Aug)
• learnfromerror: Roger Berger on Stephen Senn’s “Blood Simple” w/response by Senn (1 yr ago): http://t.co/OZn7advOlo (1 Aug)