Course Description

The basic linear algebra of matrices used for solutions of large-scale systems of linear equations is treated. Applications of matrices such as Leontieff models of multi-sector economics and the basics of the simplex method for solving linear economic optimization problems are discussed. Fundamental concepts of probability including basic combinatorial methods for probabilistic computations are studied. An introduction is given to decision theory. This treatment is in the context of Bayesian or statistical decision theory, though game theoretic versions may be discussed. Possible optional topics may include elementary Markov chains or the matrix algebra of spreadsheet operations.

Prerequisites

• MATH 141, MATH 151, MATH 155, or MATH 380 with a grade of 'C' or better or score of 5 on the Math Placement Test.

Course Reviews

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