Talking about behavioral big data is one thing. Analyzing it is another. But generating it? I wrote about my personal experience with a wearable device in the blog post Experimenting with quantified self: two months hooked up to a fitness band
Experimenting with quantitative self
Knock-knock: Forecasting MOOC opening in a week!
The Business Analytics Using Forecasting free online course (MOOC) that I designed is opening in a week! As of today, 3000+ learners have joined from around the world and all ages. The welcome discussion board reveals an amazing crowd of grad students, professionals in a variety of fields, and even instructors.
Together with our excellent team of PhD students (Tonny Kuo, Nicholas Danks, Mahsa Ashouri, and Suneel Chatla) and the NTHU studio team, we've been working tirelessly to create a great resources and a meaningful learning experience.
My colleague Ron Kenett forecasted that the course will have 10,000 learners. If you have a different forecast, please cast it now on Twitter (tag @gshmueli and use hashtag #FLbizanalytics)! The most accurate forecast for the number or learners as of midnight Oct 17, 2016 (according to the FutureLearn clock) will receive a free Practical Time Series Forecasting: A Hands-On Guide" Kindle book (the R or XLMiner edition).
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]
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.
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!