Translations*
Archived Versions

15.060 Data, Models, and Decisions

As taught in: Fall 2007

A decision tree diagram.

This course uses tools such as decision trees to draw conclusions from data. (Figure by MIT OpenCourseWare, adapted from the Data, Models, and Decisions textbook.)

Level:

Graduate

Instructors:

Prof. David Gamarnik

Prof. Robert Freund

Prof. Andreas Schulz

Course Features

Course Description

This course is designed to introduce first-year MBA students to the fundamental quantitative techniques of using data to make informed management decisions. In particular, the course focuses on various ways of modeling, or thinking structurally about, decision problems in order to enhance decision-making skills. Topics include decision analysis, probability, random variables, statistical estimation, regression, simulation, linear optimization, as well as nonlinear and discrete optimization. Management cases are used extensively to illustrate the practical use of modeling tools to improve the management practice.


*Some translations represent previous versions of courses.