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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 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