August 14, 2016

Just out: New Editions of Practical Time Series Forecasting (R and XLMiner)

I am glad to announce that the new editions of Practical Time Series Forecasting with R (Shmueli & Lichtendahl, Second Edition) and Practical Time Series Forecasting (Shmueli, Third Edition) are now available in print and ebook formats. The books are printed in the United States, Europe and India and are vailable globally. Kindle editions are also available worldwide.

Based on feedback from readers and instructors, the new editions have two main improvements: Better structuring of the topics and the addition and expansion of several topics. The two books are now aligned with each other, offering instructors the flexibility to teach a mixed crowd of programmers and non-programmers.

If you are an instructor considering the adoption of one of these textbooks for your forecasting course, fill the evaluation copy request form.

July 26, 2016

Offering a FutureLearn MOOC on Forecasting

I'll be offering a six-week free massive open online course (MOOC) on Business Analytics Using Forecasting starting October 17. This will be NTHU's first English-language MOOC hosted on the slick FutureLearn platform.

The course provides an introduction to forecasting in a business context, and is suitable for those with basic knowledge of Excel or R, and linear regression. If you have a copy of the latest edition of my Practical Time Series Forecasting books, the MOOC is a great opportunity to get started.

For more information and to pre-enroll visit the course home page.

Feel free to share with colleagues, students, and friends!

July 20, 2016

Just published: "Analyzing Behavioral Big Data: Methodological, Practical, Ethical, and Moral Issues"

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.

May 14, 2016

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.

April 28, 2016

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.

The third edition is available in hardcover and as an eBook (Kindle and Wiley e-Text). Instructors interested in an evaluation copy, please use the official Wiley page.