Management Science : This course consists of two parts: (i) The first half of the course focuses on probabilistic and statistical foundations of data analytics. At the end of this part, students will have the mathematical knowledge in following topics: probabilities, random variables, the Central Limit Theorem; prior and posterior distributions, and Bayes’ rule; correlation, and Sampling. (ii) The second half of the course focuses on mathematical foundations of decision analytics. At the end of this part, students will have the mathematical knowledge in following topics: linear algebra; calculus of several variables; convexity; separating hyperplanes; unconstrained and constrained optimization; lagrange multipliers.
Terms: Summer 2019
Instructors: Gumus, Mehmet (Summer)
**Due to the intensive nature of this course, the standard add/drop and withdrawal deadlines do not apply. Course Add is the second lecture day.
**No web drop allowed.
**Web withdrawal not applicable.