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# Math 125: Elementary Linear Algebra for Business

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### Course Description

This course is an introduction to systems of linear equations, matrices, liner programming problems, vector spaces, and more, with emphasis on business applications.

### Credit Awarded

5 hours of credit

### Course Materials

#### Textbook

Finite Mathematics & Its Applications (12th Edition), by Larry J. Goldstein, David I. Schneider, Martha J. Siegel, and Steven Hair.  Custom edition (available only from the UIC Bookstore) includes only sections covered in this course.

Note that a MyLab Math code is required for the course while the printed textbook is optional.

#### MyLab Math

A MyLab Math code linked to your Blackboard account is required for this course.  To ensure your MyLab Math code is properly linked to your blackboard account you should either:

• Purchase your MyLab Math code through the link in Blackboard.  This purchase also includes an electronic version of the textbook, you are not required to buy a printed copy.
• Make sure to link your MyLab Math account to your Blackboard account by logging into Blackboard and following the link to enter your access code.  Make sure not to use the access code for any other purpose before doing this.

If you wish to buy a printed copy of the textbook, a bundle including both the the printed textbook and MyLab Math access code is available from the UIC Bookstore.  You may instead wish to purchase a MyLab Math code via the link in Blackboard and buy a used textbook.

#### Calculator

A graphing calculator such as TI-83, TI-83 , TI-84 or TI-84 is required . It may be used on exams. Models such as the TI-nSpire are not recommended, nor are Casio and other manufacturers. The TI-83/84 model will be demonstrated in class.

The following topics are cover in Math 125
Section Topic
1.1 Coordinate Systems and Graphs
1.2 The Slope of a Straight Line
1.3 The Intersection Point of a Pair of Lines
1.4 The Method of Least Squares
2.1 Systems of Linear Equations with Unique Solutions
2.2 General Systems of Linear Equations
2.3 Arithmetic Operations on Matrices
2.4 The Inverse of a Square Matrix
2.5 The Gauss-Jordan Method for Calculating Inverses
2.6 Input-Output Analysis
3.1 Linear Inequalities
3.2 A Linear Programming Problem
3.3 Fundamental Theorem of Linear Programming
3.4 Linear Programming
4.1 Slack Variables and the Simplex Tableau
4.2 The Simplex Method I: Maximum Problems
4.3 The Simplex Method II: Nonstandard and Minimum Problems
4.4 Sensitivity Analysis and Matrix Formulations of Linear Programming Problems
4.5 Duality
6.1 Experiments, Outcomes, Sample Spaces, and Events
6.2 Assignment of Probabilities
6.3 Calculating Probabilities of Events
8.1 The Transition Matrix
8.2 Regular Stochastic Matrices
8.3 Absorbing Stochastic Matrices