Data science has altered decision making in many business scenes, from tech companies to financial institutions. This course provides fundamental statistical knowledge and practice, essential to data science in modern business enterprise. Examples are drawn from economics, finance, revenue management, pricing strategies, supply chain management, marketing, accounting, and more. Microsoft Excel will be used for calculation. The course is largely divided into three parts: (1) probability theory for decision making, (2) statistical tools to learn from data, and (3) linear regression for prediction.
No undergrads. Non-Booth graduate students with instructor permission only.
There is no required textbook. Lecture notes will be available on Canvas.
Grades are based on the midterm exam and the final exam. No auditors.
Description and/or course criteria last updated: August 07 2023
