News

September 22, 2016

Paper on A Generalized Stochastic Process For Count Data now published

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]


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.


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