I'm excited to announce that our book Information Quality - The Potential of Analytics to Generate Knowledge (with Ron Kenett) is finally out just in time for the new year. The book introduces the Information Quality (InfoQ) framework, which is useful for evaluating the potential or usefulness of a dataset for answering a specific question or goal, given the use of data analysis (statistical modeling, data mining, etc.). It is also useful for evaluating studies that use data analysis.

Here's another neat use of the COM-Poisson distribution (a distribution for count data that includes as special cases Poisson, Bernoulli, and geometric distributions): a count data process! Useful for count data that are over- or under-dispersed.
Our co-authored paper Bridging the Gap: A Generalized Stochastic Process For Count Data (with Li Zhu, Kim Sellers and Darcy Morris) is now published in The American Statistician.

[The link provides free access to the first 50 readers]

My paper (with discussion by 4 sets of authors and a rejoinder) that just came out in Quality Engineering, is aimed at introducing the community of industrial statisticians to the different challenges, opportunities and issues in analyzing "Big Behavioral Data" (BBD).

I'm glad to announce that the third edition of our textbook Data Mining for Business Analytics (with Peter Bruce and Nitin Patel) is now available! We added several cool and useful new topics: ensembles, uplift modeling, collaborative filtering, social network analysis, and text mining. The new edition also includes new examples and cases and XLMiner screenshots updated with the current software version.