MAT 240 FINITE MATHEMATICS (3 credits )
2002 Fall Semester
Dr. B. Zinn
Course Description
This course is designed to provide students with the ability, skill and confidence to use
mathematical models. Probability theory provides the logical basis for deciding among the
various interpretations of data. Matrix algebra merits attention not only because of the
existence of many important matrix models but also because it is an important tool in the
manipulation of linear systems. Linear programming is a mathematical procedure for solving
problems related to decision making and has a variety of useful applications.
Texts
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Finite Mathematics 3rd ed. Maki, D. P & Thompson, M. (1989)
Pre-Calculus Mathematics 5th ed. Sobel, M. and Lerner, N. (1995)
Applied Mathematics: For Business, Economics and the Social Sciences
Hughs, A.
Course Outline
Session 1&2:
Sets, partitions & tree diagrams
Session 3:
Basic concepts of probability: equally likely events
Session 4:
Counting techniques and combinatorics
Session 5:
Conditional probability; Independence
Session 6:
MIDTERM
Session 7:
Bayes Rule
Session 8:
Random Variables
Session 9:
Probability Distribution
Session 10&11:
Vectors and matrices, Linear systems of equations
Session 12:
Linear programming
Session 13:
Review and integration of skills
Session 14:
FINAL EXAM