## MGMT 111 - Finite Mathematics

This course provides an instruction in linear systems, linear programming, matrices, set theory, permutation and combinations, symbolic logic and switching networks, discrete probability and probability distributions, Markov chains and theory of games, and arithmetic and geometric progression. It satisfies some of the mathematics requirements for students of Business, Management, biological and social sciences, computer science and technology and information systems.

Credits: 3

Hours: 45 (Lecture Hours: 45)

Total Weeks: 15

Prerequisites:

One of Principles of Mathematics 11, Foundations of Mathematics 11, Pre-Calculus 11, CCP Math 040 or equivalent.

Non-Course Prerequisites:

None

Co-Requisites:

None

Course Content:
- Straight Lines and Linear Functions
- Systems of Linear Equations and Matrices
- Linear Programming: A Geometric Approach
- Linear Programming: An Algebraic Approach
- Mathematics of Finance
- Sets and Counting
- Probability

- Markov Chains and the Theory of Games

Learning Outcomes:
Upon successful completion of this course, the student should be able to:
- Identify linear and quadratic functions, equations, and the slope of a line.
- Conduct a break even analysis.
- Solve and manipulate systems of linear equations, using matrices and matrix operations.
- Perform linear programming operations.
- Distinguish between permutations and combinations, conditional probability and independence.
- Define sample spaces, events and probability.
- Produce a bar graph, pie chart, and graph. Draw a histogram.
- Explain measures of central tendency and dispersion.
- Recognize various probability distributions and use them to solve problems.
- Use decision-making theories.

- Recognize and apply the properties of Markov chains.