Understanding Citation Indices

Some love them, some hate them, but citation indices are heartily gobbled up by administrators in tenure and promotion decisions.  Here is Anirban DasGupta explaining the Citation Indices:

http://bulletin.imstat.org/2013/02/anirban%E2%80%99s-angle-understanding-citation-indices/

A World Without Referees

Every researcher has many stories about having papers rejected because of unfair referee reports. This happens because the refereeing process is very noisy, time consuming and arbitrary. Here is Larry Wasserman, sharing his views about the same:

www.stat.cmu.edu/~larry/Peer-Review.pdf

IMS Bulletin Editor, Dimitris Politis writes about the psychoanalytic angle of the same:

http://bulletin.imstat.org/2013/02/refereeing-and-psychoanalysis/

Overlapping Histogram in R

Just like plot and line can be used to create overlapping plots, here is a link explaining a trick to do similar overlapping for histograms:

http://www.r-bloggers.com/overlapping-histogram-in-r/

ASA Statistical Significance Series

The American Statistical Association’s (ASA) “Statistical Significance” series highlights the important contributions that statisticians make to society - from health care and the economy to national security and the environment:

http://www.statistics2013.org/asa-statistical-significance/

Royal Statistical Society’s 2013 honours announced

The RSS has announced its honours (which includes Guy medals) for 2013, having been decided by Council in January. The awards will be presented to the recipients at a ceremony held during the Society’s annual conference in Newcastle on 3 September 2013:

http://www.rssenews.org.uk/2013/02/royal-statistical-societys-2013-honours-announced/?utm_source=rss&utm_medium=rss&utm_campaign=royal-statistical-societys-2013-honours-announced

Essay Competition for Young Statisticians

In honor of the 150th anniversary of Politecnico di Milano a competition leading to a BarCamp has been organised for young (< 33 years) statisticians to envision statistical models and methods that will have an impact on the development of technology in the next 25 years. For more details have a look at:

http://mox.polimi.it/barcamp_sco2013/

Handling large number of data files

What if you have 100s of data files to be used for a single project? Isn't it annoying to read each data file individually in your workspace?

Here is use of native functions to handle the problem:
http://www.r-bloggers.com/make-your-date-folder-clean-with-function-unzip-unz/?utm_source=twitterfeed&utm_medium=twitter&utm_campaign=Feed%3A+RBloggers+%28R+bloggers%29

Useful R packages for data scientists

10 R packages every data scientist should know about:

http://blog.revolutionanalytics.com/2013/02/10-r-packages-every-data-scientist-should-know-about.html

Free e-book: Introduction to Data Science

The book by Jeffrey Stanton provides non-technical readers with a gentle introduction to essential concepts and activities of data science. For more technical readers, the book provides explanations and code for a range of interesting applications using R. Download at:

http://jsresearch.net/groups/teachdatascience/

Calculating large correlation matrices in R

Problem allocating large correlation matrices, specially for gene expression data, in R? Have a look at:

http://www.r-bloggers.com/bigcor-large-correlation-matrices-in-r/