MA 103 Course Description

MA103 FINITE MATHEMATICS (4 Cr.)

COURSE DESCRIPTION

Satisfies the foundations of natural science- mathematics requirement [Division III]

Prerequisite: MA 100 (Passed with C- or better) or satisfactory score on the Math Placement Exam. A graphing calculator or equivalent software is required.

Offered: Fall, Winter, Summer

General Introduction
The course covers linear equations, systems of linear equations, matrices, inequalities, linear programming, functions, the mathematics of finance, permutations, combinations and probability.

This course is designed primarily for students in business, economics, management, and the social sciences and life sciences. MA 103 builds on the algebraic skills of MA 100 while emphasizing applications, modeling, and decision-making from business, social and natural sciences, medicine, and other areas. It is a prerequisite for MA 171 and can be used as a Liberal Studies elective under Division III Natural Sciences/Mathematics.

Course Content

  1. Review of Algebra
    1. Polynomials and rational expressions
    2. Solving equations and inequalities
    3. Exponents and radicals
  2. Linear Functions
    1. Equations of lines
    2. Functional notation and definitions
    3. Linear functions and models
    4. Math models and curve fitting
  3. Matrices
    1. Definitions and applications for matrices
    2. Solving systems of equations using matrices
    3. Operations with matrices and finding inverses
    4. Modeling and solving problems using matrices
  4. Linear Programming
    1. Graphing linear inequalities
    2. Solving linear programming problems graphically
    3. Modeling and solving linear programming applications
  5. Finance
    1. Simple and compound interest
    2. Geometric sequences and annuities
    3. Loans and amortization
    4. Present value of future money
  6. Probability
    1. Notation, Venn diagrams, counting techniques
    2. Probability of simple and compound events
    3. Conditional probability
    4. Bernoulli trials
    5. Probability distributions of random variables; means (or expected values)
  7. Introductory Statistics
    1. Graphical representations of data-sets, frequency tables
    2. Numerical summaries of data-sets