Data sets used in business statistics, data mining, machine learning and other courses are drawn overwhelmingly from U.S. sources (or are synthetic). Data sets can serve the dual purpose of (1) bringing international data into the classroom; and (2) illustrating important business data-driven decision-making principles. Data sets meet the following criteria:
- The data is international. This goes beyond just having an international source. For instance, the data could facilitate one of the following:
- Understanding of the context (cultural, historical, economic, or institutional) within which the data was generated;
- Cross-country comparisons;
- Acquisition of knowledge of some aspect of doing business internationally (e.g. exchange rate fluctuations).
- The data is suitable for classroom use in an undergraduate or master’s level business course, illustrating some relevant business management, or data-driven decision-making principle.
- The data set is accompanied by a short teaching note detailing how it should be used. The note discusses (a) the kinds of analysis that could be done with the data (linear or logistic regression, cluster analysis, deep learning, etc.); and also (b) describe possible classroom uses (e.g. the business principles it could be used to illustrate).
In the academic year 2019-20, the Center for Global Business selected the Eve_Firms data set ("Where a founder is from affects how they structure their company") from David Waguespack, associate professor of the management and organization department at the Robert H. Smith School of Business.
The following are available for download: