An A/B test is a very simple controlled experiment where one group is subject to a new treatment (often group "B") and the other group (often group "A") is considered a control group. The classic example is attempting to compare defect rates of two production processes (the current process, and perhaps a new machine).
by Sean Wells, Senior Software Engineer, Microsoft and David Russell
DeployR exists to solve a number of fundamental R analytics integration problems faced by application developers. For example, have you ever wondered how you might execute an R script from within a Web-based dashboard, an enterprise middleware solution, or a mobile application? DeployR makes it very simple. In fact, DeployR makes it very simple for any application developed in any language to:
Sometimes the oldest technologies need a revamp. Bearings have been with us since machines were invented, but have largely kept the same design: rolling speres between two concentric rings, separated by a retainer to keep them from rubbing together. But it turns out that a simple tweak eliminates the need for the retainer, while reducing friction tenfold:
This note warns about potentially misleading results when using the use=pairwise.complete.obs and related options in R’s cor and cov functions. Pitfalls are illustrated using a very simple pathological example followed by a brief list of alternative ways to deal with missing data and some references about them.
For anyone who works with financial data and has access to a Bloomberg terminal, there is a new R package to interface to Bloomberg data services: RBlpapi. (If you had searched for an R connection to Bloomberg you wouldn’t have found this one — Bloomberg is happy to have software that connects to its public API, but not to use its name, apparently.)