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MGSC 660 Mathematical and Statistical Foundations for Analytics (3 credits)

Note: This is the 2020–2021 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .

Offered by: Management (Desautels Faculty of Management)

Administered by: Graduate Studies

Overview

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 2021

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 third lecture day.

  • **No web drop allowed.

  • **Web withdrawal not applicable.

  • **Web ADD only

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