Links related to Business Analytics
The development of the field of Business Analytics is closely related to the development of the broader field of Data Science. The Wikipedia article on Data Science (http://en.wikipedia.org/wiki/Data_science) traces its development over the last decade from an article by Bill Cleveland in 2001 entitled Data Science: An Action Plan for Expanding the Technical Areas of the Field of Statistics (http://www.jstor.org.ezproxy.library.yorku.ca/stable/1403527) to recent developments including the surge of interest in the analysis of 'big data'.
It would be interesting to consider the creation of a program or stream in 'Data Science' or 'Data Analytics' building on our current offerings.
Schulich MSc in Business Analytics
- Schulich MSc in Business Analytics (http://www.schulich.yorku.ca/client/schulich/Schulich_LP4W_LND_WebStation.nsf/page/MSc+in+Business+Analytics!OpenDocument)
- An article entitled "Big data, big analytics, big opportunity" (http://www.r-bloggers.com/big-data-big-analytics-big-opportunity/) by Murtaza Haider who is an Associate Dean at the Ted Rogers School of Management at Ryerson University.
- Aric Labarr (2012) "The Emergence of Analytics in the World of Business Decisionmaking" AMSTATNEWS (http://magazine.amstat.org/blog/2012/09/01/analyticssept2012/)
- Wikipedia on Business Analytics (http://en.wikipedia.org/wiki/Business_analytics)
- Society of Actuaries: Actuaries in Advanced Business Analytics (http://www.soa.org/leadership/current-initiatives/analytics-seminar-rfi.aspx)
- A job ad at the JSM 2012 (http://www.math.yorku.ca/people/georges/Files/Statistics_Curriculum/TravellersAd_JSM2012.jpg) and link (https://www.travelers.com/about-us/careers/development-programs/actuarial-science.aspx?utm_source=hiringevent&utm_campaign=AALDP_QR_Branding_Drive)
- Simpson's Paradox and Business Analytics: This very interesting article (http://www.significancemagazine.org/details/webexclusive/2671151/Simpsons-Paradox-A-Cautionary-Tale-in-Advanced-Analytics.html) in the magazine Significance shows a number of real data examples, including business examples, where the 'wrong' statistical analysis would lead to wrong conclusions about the causal effect between two variables. Here's a tantalizing excerpt: