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Title : 15.060 Data, Models, and Decisions (MIT)

Title : 15.060 Data, Models, and Decisions (MIT)

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.

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.

Fromsemester : Fall

Fromsemester : Fall

Fromyear : 2007

Fromyear : 2007

Creator :

Creator :

Creator :

Creator :

Creator :

Creator :

Date : 2008-07-16T01:22:20+05:00

Date : 2008-07-16T01:22:20+05:00

Relation : 15.060

Relation : 15.060

Language : en-US

Language : en-US

Subject : decision analysis

Subject : decision analysis

Subject : discrete probability distributions

Subject : discrete probability distributions

Subject : continuous probability distributions

Subject : continuous probability distributions

Subject : normal probability distribution

Subject : normal probability distribution

Subject : statistical sampling

Subject : statistical sampling

Subject : regression models

Subject : regression models

Subject : linear optimization

Subject : linear optimization

Subject : nonlinear optimization

Subject : nonlinear optimization

Subject : discrete optimization

Subject : discrete optimization