# CSC 202 - Discrete Mathematics for Computer Scientists II

## Homepage: http://www.stonehill.edu/compsci/shai.htm

Lectures:  MWF 2:30 - 3:45,  215 College Center
Pettofrezzo, Anthony J. Matrices and Transformations. New York: Dover, 1978.
Exams:  There will be 6 quizzes (25%), the lowest grade will be dropped, and one final examination (35%).  The final examination will be Monday May 6, 11:30 AM.

Teaching Assistant:  Theo Slepski  There will be help sessions weekly Tuesday and Wednesday 7-9 in the lab.

Assignments:  Homeworks are worth 40% of your grade.   You may do these with a partner, and one grade will be given to both people in the group.  Read our department's academic integrity guidelines before you hand in any written work.

Grading:  Your grade is 25% quizzes, 40% homework, and 35% exam.  You can guarantee an A- or better with 90%, a B- or better with 80% etc.  I may curve these numbers in your favor, if I feel it is warranted.

Goals:  To understand the mathematics that underlies computer science, and to appreciate where it is used.  Last semester concentrated on functions, number theory, recurrence equations, recursion, combinatorics, and their applications.  This semester concentrates on sets, graphs, Boolean algebra, linear algebra, and their applications.

Special Dates:  None.

Description: The two semester discrete math sequence covers the mathematical topics most directly related to computer science. Topics include: logic, relations, functions, basic set theory, countability and counting arguments, proof techniques, mathematical induction, graph theory, combinatorics, discrete probability, recursion, recurrence relations, linear algebra, and number theory. Emphasis will be placed on providing a context for the application of the mathematics within computer science. The analysis of algorithms requires the ability to count the number of operations in an algorithm. Recursive algorithms in particular depend on the solution to a recurrence equation, and a proof of correctness by mathematical induction. The design of a digital circuit requires the knowledge of Boolean algebra. Software engineering uses sets, graphs, trees and other data structures. Number theory is at the heart of secure messaging systems and cryptography. Logic is used in AI research in theorem proving and in database query systems. Proofs by induction and the more general notions of mathematical proof are ubiquitous in theory of computation, compiler design and formal grammars. Probabilistic notions crop up in architectural trade-offs in hardware design.  Linear algebra has a vast variety of applications including: Markov chains, cryptography,  computer graphics, curve fitting, electrical circuits, and data mining.  The first semester concentrates on induction, proofs, combinatorics, recurrence relations, computational complexity, Big-O, and number theory.  The second semester concentrates on logic, sets, set algebra, countability, functions, Boolean algebra, linear algebra and applications.