- Professor Ramon van Handel of Princeton University posts his lecture notes on Probability in High Dimension.
- Everday Anayltics shares his experience as a statistical consultant on a project for Delta Airline data using PCA and K-means Clustering.
- If you know R and want to improve your SAS skills (or the other way around), check out this tutorial on logistic regressions using both packages.
- Do you trade stocks? If so, here is A Simple Shiny App for Monitoring Trading Strategies.
- Maybe I Don’t Really Know R After All.
- And finally, why we should Separate Statistical Models of “What Is Learned” from “How It Is Learned”.
- If you are on the job market, Tal Galili from R bloggers has compiled 3 new R jobs for seekers like you.
- Text mining is currently a live issue in data analysis. Enoromus text data resourses on the Internet made it an important component of Big Data world. If text mining is something that you need to do for your job, you should read Text mining in R – Automatic categorization of Wikipedia articles.
- Randy Olsen, PhD student at Michigan State University’s Computer Science program, studies the percentages of undergraduate degrees conferred to men in the USA and publishes his findings in a blog titled The double-edged sword of gender equality.
- Who will win the World Cup? See what statisticians say.
- Earlier this month, the results of the 15th annual KDnuggets Software Poll were released and R’s popularity continues to grow. See Revolution Analytics’ new post for details.
- And finally, Xi’an discusses a new paper by Simon Barthelmé and Nicolas Chopin called The Poisson transform for unnormalised statistical models.
- Writing functions is an important part of programming, and in order to write proper functions you need to know how to debug when your functions aren’t working. Slawa Rokicki, PhD student at Harvard, explains How to write and debug an R function.
- It is often said that you should avoid loops in R because R is extremely slow with iterations, and hence many R-programmers try to avoid loops by working with matrices and arrays. Did you know that an even better option is to run your loops in C++ and import your result back into R? Here is a quick tutorial called how you can use C++ within R.
- Rasmus Bååth blogs about the The Most Comprehensive Review of Comic Books Teaching Statistics.
- Did you know that more and more startups are starting to use R as their primary data analysis tool? According to Revolution Analytics, Uber and CultureAmp have just joined the R camp.
- Xi’an reviews a new paper called Generalizations related to hypothesis testing with the Posterior distribution of the Likelihood Ratio by Smith and Ferrari.
- And finally, DiffusePrioR writes “If history can tell us anything about the World Cup, it’s that the host nation has an advantage of all other teams”. Do you agree or disagree, and what do you think is Brazil’s chance of winning the World Cup?
- Like the plots above? Learn how to create these in R from Freakonometrics’ new post called Box plot, Fisher’s style.
- If you are on the job market, Tal Galili from R bloggers has compiled 6 new R jobs for seekers like you.
- Big Data has gained lots of popularity recently, and every data scientist should know at least something about it. If you are new to data science, consider this introduction to R for Big Data with PivotalR.
- Using Repeated Measures to Remove Artifacts from Longitudinal Data by Dmitry Grapov.
- And finally, Andrew Gelman discusses Why we hate stepwise regression.
- 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?