SYLLABUS

MAT 119 – FINITE MATHEMATICS

Lead Instructor: Richard Diefenbach Office: J1013

Phone: 618/634-3317 E-mail: Richardd@shawnee.cc.il.us

Credit Hours: Three (3) semester hours

Prerequisites: College Algebra (Mat 116) or Pre-calculus (Mat 115) with a grade of “C” or better

Course Description:

Introductory course in analysis for business, life science, and social science students. This course includes set theory, counting and elementary probability theory, systems of linear equations, finite Markov chains, systems of inequalities and introduction to linear programming and statistics. Graphing calculators will be used in this class Prerequisites: College Algebra - MAT 116 with a grade of "C" of better

Textbook(s) and Supporting Materials:

Finite Mathematics for the Managerial, Life, and Social Sciences, 7^th edition, S.T.Tan (Brooks/Coles Publishing Co.) Pacific Groove, CA 2003

Course Objectives:

A. To acquaint the student with some of the mathematical equipment needed in our increasingly quantified world.

B. To provide examples and illustrations from social science, business, education, economics, and other areas.

C. To equip the student with methods of solving systems of linear equations.

D. To equip the student with an understanding of the basics of matrices.

E. To acquaint the student with the basics of set theory.

F. To provide instruction in counting, combinations and permutations in such a way that the student will have a working understanding of these theories.

G. To equip the student with an understanding of the basics in the meanings and rules of probability.

H. To equip the student with some of the more useful statistical tools.

I. To look into specific (but appropriate) areas of business, finance, social science, and others to illustrate how the mathematical tools covered in this course can be applied.

Instructional Modes:

Lectures, class discussions and demonstrations will be used to develop and analyze the desired topics. Student involvement will be an ongoing affair.

Outside reading and associated activities will be encouraged and rewarded.

The use of graphing calculators will be required. A Texas Instrument TI-83 is recommended. There are a limited number of calculators for loan on a first come basis.

The computer will be utilized when appropriate.

Student Evaluation/Outcome Assessment Measures:

Hour tests, a comprehensive final examination, and homework collections will provide the means of determining the final grade. Hour tests will count 100 points each; the final exam 200 points; and homework 20 points each.

***Specifics on the grading procedure and/or a tentative course schedule, developed by the instructor, may accompany this syllabus.

Attendance Policy:

Each student is expected to attend all class meetings. The student is expected to be on time and ready to begin class with the proper materials at the beginning of each class period. If a student will be unable to attend class, it is their responsibility to contact the instructor to obtain homework assignments and other information.

Topical Outline:

Chapter 1: Straight Lines and Linear Functions

1.1 The Cartesian Coordinate System

1.2 Straight Lines

1.3 Linear Functions and Mathematical Models

1.4 Intersections of Straight Lines

Chapter 2: Systems of Linear Equations and Matrices

2.1 Systems of Linear Equation -- Introduction

2.2 Solving Systems of Linear Equations I.

2.3 Solving Systems of Linear Equations II.

2.4 Matrices

2.5 Multiplication of Matrices

2.6 The Inverse of a Square Matrix

Chapter 3: Linear Programming: A Geometric Approach

3.1 Graphing Systems of Linear Inequalities in Two Variables

3.2 Linear Programming Problems

3.3 Graphical Solution of Linear Programming Problems

Chapter 4: Linear Programming: An Algebraic Approach

4.1 The Simplex Method: Standard Maximization Problems

4.2 The Simplex Method: Standard Minimization Problems

Chapter 6: Sets and Counting

6.1 Sets and Set Operations

6.2 The Number of elements in a Finite Set

6.3 The Multiplication Principle

6.4 Permutations and Combinations

Chapter 7: Probability

7.1 Experiments, Sample Spaces, and Events

7.2 Definition of Probability

7.3 Rules of Probability

7.4 Use of Counting Techniques in Probability

7.5 Conditional Probability and Independent Events

Chapter 8: Probability Distributions and Statistics

8.1 Distributions of Random Variables

8.2 Expected Value

8.3 Variance and Standard Deviation

8.4 The Binomial Distribution

8.5 The Normal Distribution

Chapter 9: Markov Chains and the Theory of Games

9.1 Markov Chains

9.2 Regular Markov Chains

9.3 Absorbing Markov Chains (if time permits)

9.4 Game Theory and Strictly Determined Games ( if time permits)

NOTE: The above schedule and procedures in this course are subject to change in the event of extenuating circumstances.

Instructor’s Page: