Catalog Description: 
This course is designed to highlight discrete (noncontinuous) mathematical structures, with a
strong emphasis on practical algorithms and a significant computer applications component. Topics
include: algorithms, financial models, recursion, recurrence relations, functions, set theory,
countability, counting arguments, number representation, logic, proof techniques, mathematical
induction, and graph theory. Meets General Education Mathematical
Sciences requirement. (Offered spring semester only.)

Prerequisites: 
Passing score on a placement exam given during the first
week of class. Students who do not do well on the placement exam are advised to take MATH 102,
followed by MATH 180 in a subsequent semester.

Required Course Materials: 
Goodaire and Parmenter, Discrete Mathematics with Graph Theory, 3^{rd} edition, Pearson Prentice Hall, 2006 (ISBN: 9780131679955)

Course Coordinator: 
Lamarr C. Widmer, Ph.D., Professor of Mathematics

Course Audience: 
Students in the Information Sciences major or students wishing to meet their General Education mathematical sciences requirement through a course that emphasizes mathematics related to computing.

Course Objectives: 
By completion of the course students will demonstrate facility with:
 Iterative & recursive algorithms, including recurrence relations.
 Discrete data structures such as sets, relations, discrete functions, graphs and trees.
 Number representations, including binary and hexadecimal.
 Propositional and predicate logic on which mathematical reasoning is based, including the use of formal tools of symbolic logic.
 Boolean algebra.
 Reading and constructing valid mathematical arguments (proofs) and understanding mathematical statements (theorems), including proof by mathematical induction.
General Education: By the completion of this course, the student will demonstrate the ability to:
 Identify methods and assumptions of the mathematical sciences.
 Understand at least one of the three mathematical sciences of computing, mathematics and statistics from a liberal arts perspective.
 Think logically, analytically and abstractly through engagement in quantitative problemsolving activities.
 Identify key elements of communication within a variety of contexts.

Topics: 
Topics
include: algorithms, financial models, recursion, recurrence relations, functions, set theory,
countability, counting arguments, number representation, logic, proof techniques, mathematical
induction, and graph theory.

