Five years ago, in 2012, I decided to experiment in improving my teaching by creating a flipped classroom (and semi-MOOC) for my course “Business Analytics Using Data Mining” (BADM) at the Indian School of Business. I initially designed the course at University of Maryland’s Smith School of Business in 2005 and taught it until 2010. When I joined ISB in 2011 I started teaching multiple sections of BADM (which was started by Ravi Bapna in 2006), and the course was fast growing in popularity. Repeating the same lectures in multiple course sections made me realize it was time for scale! … Continue reading My videos for “Business Analytics using Data Mining” now publicly available!
My first semester at NTHU has been a great learning experience. I introduced and taught two new courses in our new Business Analytics concentration (data mining and forecasting). Both courses met once a week for a 3-hour session for a full semester (18 weeks). Although I’ve taught these courses in different forms, in different countries, and to different audiences, I had a special discovery this time. I discovered the critical role of the learning space on the quality of teaching and learning. Specifically for a topic that combines technical, creativity and communication skills. “Case study” classroom In my many years of experience … Continue reading Teaching spaces: “Analytics in a Studio”
The American Statistical Association published new “Curriculum Guidelines for Undergraduate Programs in Statistical Science“. This is the first update to the guidelines since 2000. The executive summary lists the key points: Increased importance of data science Real applications More diverse models and approaches Ability to communicate This set sounds right on target with what is expected of statisticians in industry (the authors of the report include prominent statisticians in industry). It highlights the current narrow focus of statistics programs as well as their lack of real-world usability. I found three notable mentions in the descriptions of the above points: Point … Continue reading New curriculum design guidelines by American Statistical Association: Who will teach?
But what exactly does this mean? In the recent ISIS conference, I organized and moderated a panel called “Business Analytics and Big Data: How it affects Business School Research and Teaching“. The goal was to tackle the ambiguity in the terms “Business Analytics” and “Big Data” in the context of business school research and teaching. I opened with a few points: Some research b-schools are posting job ads for tenure-track faculty in “Business Analytics” (e.g., University of Maryland; Google “professor business analytics position” for plenty more). What does this mean? what is supposed to be the background of these candidates … Continue reading What does “business analytics” mean in academia?
Adopting new technology for teaching has been one of my passions, and luckily my students have been understanding even during glitches or choices that turn out to be ineffective (such as the mobile/Internet voting technology that I wrote about last year). My goal has been to use technology to make my courses more interactive: I use clickers for in-class polling (to start discussions and assess understanding, not for grading!); last year, after realizing that my students were constantly on Facebook, I finally opened a Facebook account and ran a closed FB group for out-of-class discussions; In my online courses on statistics.com … Continue reading Flipping and virtualizing learning
The recent trend among mainstream business schools is opening a graduate program or a concentration in Business Analytics (BA). Googling “MS Business Analytics” reveals lots of big players offering such programs. A few examples (among many others) are: Carnegie Mellon’s Heinz College Michigan State’s Broad School of Business NYU Stern University of Connecticut’s School of Business Rutgers Business School Drexel’s Lebow College of Business These programs are intended (aside from making money) to bridge the knowledge gap between the “data or IT team” and the business experts. Graduates should be able to lead analytics teams in companies, identifying opportunities where … Continue reading The mad rush: Masters in Analytics programs
Quantitative forecasting is an age-old discipline, highly useful across different functions of an organization: from forecasting sales and workforce demand to economic forecasting and inventory planning. Business schools have offered courses with titles such as “Time Series Forecasting”, “Forecasting Time Series Data“, “Business Forecasting“, more specialized courses such as “Demand Planning and Sales Forecasting” or even graduate programs with title “Business and Economic Forecasting“. Simple “Forecasting” is also popular. Such courses are offered at the undergraduate, graduate and even executive education. All these might convey the importance and usefulness of forecasting, but they are far from conveying the coolness of forecasting. … Continue reading Forecasting + Analytics = ?
In business schools it is common to teach statistics courses using Microsoft Excel, due to its wide accessibility and the familiarity of business students with the software. There is a large debate regarding this practice, but at this point the reality is clear: the figure that I am familiar with is about 50% of basic stat courses in b-schools use Excel and 50% use statistical software such as Minitab or JMP. Another trend is moving from offline software to “cloud computing” — Software such as www.statcrunch.com offer basic stat functions in an online, collaborative, social-networky style. Following the popularity of … Continue reading Google Spreadsheets for teaching probability?