7a. Prerequisite(s): (Course and/or other preparation/experience that is REQUIRED to be completed previous to enrollment in this course.)

Completion of Math D with grade of "C" or better, or placement by matriculation assessment process

7b. Co-requisite(s):  (Courses and/or other preparation that is REQUIRED to be taken concurrently with this course.)

7c. Advisory: (Minimum preparation RECOMMENDED in order to be successful in this course.  Also known as “Course Advisory”.)

9b. Catalog Description:

Review of functions; systems of equations; mathematics of finance; matrices and their applications; linear programming; introduction to probability and statistics; Markov Chains; and decision making. (CAN MATH 12)

10. Student Performance Outcomes: (Outcomes for all credit courses must indicate that students will learn critical thinking and will be able to apply concepts at college level.  Outcomes must be related to items listed in Section 11.)

1. Solve problems utilizing graphics of linear functions and linear inequalities.
2. Construct solutions of systems of linear equations using graphical, algebraic or matrix methods.
3. Construct solutions to linear programming problems using graphs or the Simplex Method.
4. Be able to create a frequency distribution and use it to determine mean, median, mode, variance and standard deviation.
5. Solve probability problems using combinatorics.
6. Solve probability problems which involve independent, compound and conditional events.
7. Create a probability function for a random variable and use it to answer probability questions.
8. Solve applied finance problems including compound interest, annuity payments and/or amortization.
9. Solve problems involving a Markov process.

11. Course Content Outline: (Provides a comprehensive, sequential outline of the course content, including all major subject matter and the specific body of knowledge covered.)

I. Linear Functions
a) Slope formula and linear equations
b) Linear Functions
c) Models using linear functions (associated word problems)

II. Systems of Linear Equations
a) Echelon methods for solution
b) Gauss-Jordan method for solution
c) Matrix algebra
d) Matrix inverses method of solution
e) Input-Output models (associated word problems)

III. Linear Programming - Graphical Method
a) Graph linear inequalities
b) Graphical methods for solution to linear programming problems
c) Applications (associated word problems)

IV. Linear Programming - Simplex Method
a) Introduction of slack variable, pivot element
b) Maximization problems
c) Minimization problems, duality
d) Nonstandard problems

V. Mathematics of Finance
a) Interest, simple and compound
b) Annuity evaluation
i) future value
ii) present value, amortization

VI. Sets and Probability
a) Introduction to sets
b) Venn Diagrams
c) Probability
i) basic, intersection, union
ii) conditional, independence
iii) Bayes Theorem
d) Permutations and combinations
e) Binomial probability
f) Probability distributions and expected value

VII. Statistics
a) Mean, median, and mode
b) Variance and standard deviation
c) Applications (associated word problems)

VIII. Markov Chains
a) Basic ideas, introduction
b) Regular Markov Chains

12. Typical Assignments: (List types of assignments, including library assignments.)

a. Reading Assignments: (Submit at least 2 examples)

1. Read selected topics throughout the course from the textbook, such as how to amortize a home loan based on real world data.
2. A farmer grows wheat and barley on her 500 acre farm. Each acre of wheat requires 3 days of labor to plant, tend, and harvest, while each acre of barley requires 2 days of labor. If the farmer and her hired field hands can provide no more than 1200 days of labor this year, how many acres of each crop can she grow?

b. Writing, Problem Solving or Performance: (Submit at least 2 examples)

1. Complete homework problems from the textbook on topics throughout the course. Such problems may involve algebraic computation, sketching graphs and diagrams, solving systems of equations using algebraic methods, matrices, and graphs, solving maximum and minimum problems using linear programming or the simplex method, or probability and statistics calculations.
2. Solve application problems in class. For example: evaluate different IRA models to determine which interest rate and investment style maximizes future retirement benefits.

c. Other (Terms projects, research papers, portfolios, etc.)

SECTION D

SECTION E

SECTION F

SECTION G