Pre­dict­ive Ana­lyt­ics

Course content

This course is designed to provide both a theoretical foundation for predictive modeling but also hand-on experience with analyzing economic data. The models presented in the course will belong to different fields of statistics but in all cases the predictive power of the models will be in focus. Introducing statistical tools allows us to not only come up with an actual forecast of an economic variable of interest (think e.g. of sales) but also to assess the uncertainty of the forecast. Before a proper model can be selected it is of interest to discuss issues about data availability and also data reliability. There is often negligible discussion of such topics in the text book but providing the students with examples of the types of challenges one may encounter – based on the research of the teachers – will try to fill this gap. 

Predictive analytics is a field that can provide managers with very valuable tools for decision making. Both for sales variables of firms but also for financial variables like stock prices forecasting models and methods may be of interest, and during the course we will discuss challenges in relation to preparing relevant data for forecasting, choosing well-suited models for analysis and we offer a range of tools for evaluating the forecasting performance of the models we present. In one of the lectures we introduce a tool that can be very helpful for model selection if ‘Big  Data’ is available.

The course contributes to several competences emphasized at CBS, such as emphasizing critical thinking, providing students with deep business knowledge in broad context, and being encourage students to be analytical with data and curious about ambiguity.