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). Industrial statistics is typically focused on monitoring, improving, and testing "things", but today "things" are increasingly measuring human and social behavior (e.g., phones and sensors). This change has important ramifications to researchers.
Just published: "Analyzing Behavioral Big Data: Methodological, Practical, Ethical, and Moral Issues"
Interview at Statistics Views
Statistics Views interviewed the co-authors of Data Mining for Business Analytics about the new 3rd edition and upcoming JMP edition. We talk about what made us write the book, our journey, and more.
3rd edition of "Data Mining for Business Analytics" now published
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.
We updated "business intelligence" to "business analytics" in the title of the textbook to reflect the change in terminology since the last edition.
The foreword for the third edition is by University of Minnesota's Ravi Bapna, the Carlson Chair in Business Analytics who was one of the earliest users of the first edition and has been leading and heading many business analytics programs, research, and initiatives.
Thanks to all our readers and adopting instructors who've shared feedback and suggestions over the years. This vibrant community has helped us create a better book.
"To Explain or To Predict?" in Hong Kong
If you're in Hong Kong next week and interested in my work on "To Explain or To Predict?" feel free to attend one of the two talks, each delivered to a different type of audience:
- May 4, 14:30 at the Faculty of Business & Economics at The University of Hong Kong (abstract and details) - hosted by Prof. Hsiao-Hui Lee.
- May 5, 10:30 at the Department of Systems Engineering and Engineering Management (SEEM) at City University of Hong Kong (abstract and details) - hosted by Prof. Kwok Tsui.
"To Explain or To Predict?" at NTHU's Institute of Information Systems & Applications
On Wednesday (March 23) I'll talk about the difference between using statistical models and data mining for explanation vs. prediction at NTHU's Institute of Information Systems & Applications (here's the official announcement). For those who've been waiting to hear this talk in Hsinchu, here's your chance. Looking forward to a lively discussion.
Location: NTHU, Delta Building, Room 105
Date & Time: March 23, 13:30-15:00