Math 160: Finite Mathematics for Business

Course Prerequisites

One of:

Course Description

Finite Mathematics is a course focusing on mathematical concepts that have applications to business related ideas.

Topic areas include Systems of Linear Equations, an introduction to Matrix concepts plus an Economics application, the graphing approach to Linear Programming, counting techniques with basic combinatorial calculations, probability including conditional probability, independent events, and Bayes’ Theorem, an introduction to Statistics, and an introduction to Markov processes using matrices.

There is very strong emphasis throughout the material on applications, so the student should expect the exercises to lean heavily on word problems.

There is also an emphasis on using some technology to assist in finding the answers to many exercises in many of the topic areas. This emphasis is chosen to give business degree students an opening look at how technology will likely enter into their working careers once they leave the university.

Credit Awarded

5 hours of credit

Textbook

Finite Mathematics and Its Applications, Tenth Edition by Goldstein, Schneider, and Siegel.

The course will cover most of chapters 2, 3, 5, 6, 7, and 8. The online software MyMathLab will be used with the textbook. Students are required to purchase a MyMathLab Student Access Kit and register for the appropriate course number. Students can purchase the Student Access Kit in the campus bookstore or online. A paper copy of the textbook is recommended but not required, as there is an abridged electronic version available with the MyMathLab account.

Calculator

A calculator is necessary to do many problems throughout the course. A graphing calculator such as the TI-83 or TI-84 with matrix, list and statistics capabilities is required.

Material and Resources

Course Schedule

The following is a typical 15-week Fall or Spring semester schedule for MATH 160. During the Summer sessions, the schedule is condensed into 8 weeks.
Sections Topics
Week 1

Sec. 2.1-2.2
Start Linear Algebra
Solving Systems of Linear Equations I and II
Week 2

Sec 2.3-2.4
Operations on Matrices
Inverse of a Matrix
Gauus-Jordan Method of Determining the Inverse
Week 3

Sec 2.5-2.6
Gauss-Jordan
Input-Output Analysis
Week 4

Sec 3.1-3.2
Linear Programming Introduction
Solution to Linear Programming Problems
Week 5

Sec 3.3, 5.1-5.3
Applied Linear Programming Problems
Sets and Fundamental Principle of Counting
Venn Diagrams and Counting
Week 6

Sec 5.4-5.6
Multiplication Principle
Factorials, Permutations, and Combinations
Mixed Counting Problems
Week 7

Sec 5.6-5.8
Exam 1 Review
Binomial Theorem and Applications
Partitions and Multinomial Coefficients
Week 8

Sec 6.1-6.4
Introduction to Probability
Probability Assignments and Distribution Construction
Calculating Probability of Events
Week 9

Sec 6.5-6.6
Conditional Probability and Independent Events Events
Conditional Pr
Tree Diagrams
Week 10

6.6-6.7
Bayes' Theorem
Week 11

Sec 7.1-7.2
Visual Representation of Data
Frequency and Probability Distributions
Week 12

Sec 7.2-7.4
Binomial Trials
Mean and Expected Value
Week 13

Sec 7.5-7.7
Exam 2 Review
Variance and Standard Deviation
Normal Distribution and Applications
Applications of Normal Distribution
Week 14

Sec 8.1-8.2
Transition Matrix, Markov Chains
Regular Stohastic Matrices
Week 15

8.3, Review
Absorbing Stochastic Matrices
Final Exam Review