This course is designed to highlight discrete (non-continuous) 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.)

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.

Lamarr C. Widmer, Ph.D., Associate Professor of Mathematics

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.

By completion of the course students will demonstrate facility with:

1. Iterative & recursive algorithms, including recurrence relations.
2. Discrete data structures such as sets, relations, discrete functions, graphs and trees.
3. Financial applications such as compound interest and annuities, modeled by discrete functions..
4. Basic counting principles, including permutations and combinations and uses of diagonalization and the pigeonhole principle.
5. Number representations, including binary and hexadecimal.
6. Propositional and predicate logic on which mathematical reasoning is based, including the use of formal tools of symbolic logic.
7. Boolean algebra.
8. Reading and constructing valid mathematical arguments (proofs) and understanding mathematical statements (theorems), including proof by mathematical induction.
9. Computing applications in support of the above learning objectives.

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