Here is the latest bag of tweets^*, which covers November 2014.

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

• DiegoKuonen: RT @vmirly: Bayesian thinking: update your belief after any new observation! http://t.co/KeCij3zrCU (29 Nov)
• teoliphant: Love the PyData wrap-up blogs: https://t.co/HczEEkO6F0 There is always something new and cool in #Python and @PyDataConf (28 Nov)
• frod_san: Reproducible Science with #Rmarkdown http://t.co/xYaLlC7ZxY. Slides of my talk yesterday at #SevillaR #rstats user group (27 Nov)
• SublimeTxtTips: The Best Sublime Text 3 Themes of 2014 http://t.co/BjKfP6m1yL (25 Nov)
• JeromyAnglim: “Statistics for Big Data” http://t.co/ty45aF9x0l (25 Nov)
• twiecki: New blog post: A modern guide to getting started with Data Science and Python http://t.co/pncihL61hj #datascience #pandas #python #pydata (18 Nov)
• noamross: This is great: “Beyond Power Calculations: Assessing Type S (Sign) + Type M (Magnitude) Errors” by Gelman + Carlin http://t.co/5fJ7U6xwWH (17 Nov)
• neilfws: awesome bioinformatics rant https://t.co/sVH4XWOo5G “a big ol’ list of shit with p-values” (17 Nov)
• ProcessingOrg: Download the new #Processing 3.0a5 here: https://t.co/D95EeHYk3t Release notes: https://t.co/TOuMuk5Uk2 (17 Nov)
• HackYourPhd: Check our last #OpenScience interviews with @EvoMRI: https://t.co/Sj0ANwXfgt and JB Poline: https://t.co/Ui0nmIy5QQ http://t.co/qMoX2ZVNDJ (16 Nov)
• JanWillemTulp: in case you were not able to attend: @eagereyes has a nice series of summary posts day by day of #ieeevis https://t.co/uZtCYbNugI (14 Nov)
• michaelwaskom: seaborn 0.5 is out! Check out the release notes to see what’s new: http://t.co/qdDAC2q6bA http://t.co/4aDSlWb6YD (14 Nov)
• DrBunsen: Very few statisticians write as concise and clear as Brad Efron. Case in point, Stein’s Paradox: http://t.co/gmqIFNnmxC (14 Nov)
• mja: Pitfalls of regularized machine learning in genetic prediction http://t.co/Yk688V6Dkw /ht @moorejh (14 Nov)
• eagereyes: Overview tool: http://t.co/3wcyIE66xH Source: http://t.co/FeWGkvx3mQ Blog: http://t.co/RWja6IAW2N Paper: http://t.co/XS4eMURIJu #IEEEVIS (14 Nov)
• seanjtaylor: Putting the Magic in Data Science: http://t.co/vBHSNW6ssR A blog post (with slides) about my talk at @QConSF last week. (14 Nov)
• MattDowle: Discussion and benchmarks of Stata and #Rstats : http://t.co/fCfiN4T8oT (14 Nov)
• adolfoalvarez: Third and last spam about “The free, open, and proprietary flavors of R” http://t.co/7krGknxhae #rstats (12 Nov)
• DrBunsen: glances > htop https://t.co/ZZ9HglDUlk (12 Nov)
• noamross: I wrote a post on the @swcarpentry blog about our #rstats user group and how to build a community of learners: http://t.co/v0Na2FpC8W (10 Nov)
• Stata: RT @Haghish Synlight package: #HTML syntax highlighter for #Stata at http://t.co/KNg9dhjY8Z (10 Nov)
• mja: Just learned/figured out that MCMCglmm can do multimembership random terms where multiple columns describe the same random effect. (10 Nov)
• fusaroli: comparing mixed effects models in Statsmodels (Python) and Lme4 (R): http://t.co/zuGMecVB7V (10 Nov)
• cboettig: .@gvwilson I think no. Longer answer: http://t.co/iYnj716ppT & on pandoc-discuss https://t.co/CYJL30dfbV (9 Nov)
• PythonDaily: Simple Graphing with #IPython and #Pandas http://t.co/UF83OrPgNJ #python (9 Nov)
• statalgo: “Julia: A fresh approach to numerical computing” http://t.co/q2kUiXGRzy (9 Nov)
• planet_lisp: Christophe Rhodes: reproducible builds - http://t.co/dieiA4zbpu (9 Nov)
• twiecki: Clustered heatmap lands in #seaborn https://t.co/MXPH7JpZi4 Screenshot: https://t.co/jgOuyMGZo8 by @olgabot (7 Nov)
• YhatHQ: A project based on Ebola data analysis | blackhat06/ebolabigdataorg | http://t.co/2Qm2vG111D (7 Nov)
• JonesZM: @alexhanna or in statistics. http://t.co/kgTWGSNYVD (7 Nov)
• dl4j1: Sentiment Analysis with Word2Vec: A Tutorial http://t.co/v47PeWcJao (7 Nov)
• kdnuggets: P-values, the “gold standards” of statistical validity, are not as reliable as many assume http://t.co/WdNTaPXgQp http://t.co/KegOFYHnJB (7 Nov)
• jaimetarrant: Neat, just installed Geeknote (http://t.co/sAiA9K6O82) a python app 4 cli access to @evernote -edit notes with vim, emacs! Linux/OSX/BSD’s (7 Nov)
• albertocairo: Good tutorial: Improving R Data Visualisations Through Design, by @spatialanalysis http://t.co/9iNYNhOant http://t.co/ls5wl4Anuh (7 Nov)
• DataTau: Python Statsmodels 0.6 released, with Linear Mixed Effects Models and more!: http://t.co/JnNqRtrw3P (7 Nov)
• Atabey_Kaygun: New post: Longest common subsequence of two sequences http://t.co/ED3B4hex77 (6 Nov)
• mbostock: Read more about the choropleth technique we used, where visual weight is proportional to population density: http://t.co/TXUeOvDIc3 (5 Nov)
• JennyBryan: @genetics_blog maybe you will also like twee() https://t.co/hfmYLVOgSJ (4 Nov)
• KevinQ: @JanWillemTulp http://t.co/4HtyoYRn2K (4 Nov)
• WolframResearch: Model hypothetical scenarios of a possible world-wide Ebola outbreak using Mathematica and the Wolfram Language: http://t.co/p3qFGN7wKw (4 Nov)
• StatFact: Offended by conditional probability http://t.co/wO31gOlndk (4 Nov)
• tdhopper: “This module was created to supplement Python’s itertools module, filling in gaps in areas of basic combinatorics.” http://t.co/P6r0KYZRea (3 Nov)
• YhatHQ: Deep Learning Tutorial | http://t.co/ANAbAZdBzI (3 Nov)
• UnixToolTip: Vertically align code around = signs using Emacs: M-x align-regex = (3 Nov)
• JanWillemTulp: This is good! “@mbostock: Five rules for effective scroll-based interaction: http://t.co/IpDo5LQCqU” (3 Nov)
• fusaroli: TROLLing: an open science repository for linguistic data and scripts: http://t.co/NL2OT4Td0X (3 Nov)
• Bioconductor: Course Material http://t.co/xbB9ITJDSF & some videos https://t.co/Yel5N5MqIr from the latest @Biocondcutor course (Oct 27-29) now available. (1 Nov)