Section 001: TR 10 – 11:40 AM CI 1012
Course Schedule
INSTRUCTOR
Dr. Fletcher Norris
E-mail: mailto:norris@uncw.edu?subject=CSC
133
Phone: (910) 962-3301
Office hours (CI 2025)
Tuesday - Thursday 9:30 – 10:00 AM and 1:30 – 2:00 PM and by appointment
Introduction: Welcome to CSC 133, a course in discrete structures
with an emphasis on applications to computer science. Prerequisite: MAT 111 or
MAT 115 or equivalent, Corequisite: CSC 121. A basic understanding of discrete
mathematical topics is fundamental for academic work in computer science. Many
students of this course will find they have familiarity with some of the
topics: for instance, truth tables, logical propositions, elements of set
theory, as well as basic notions of functions and mathematical induction. Prior
work in these areas is not assumed. In this course we will discover that
logical propositions are the underlying model of discrete systems. From this
modest beginning we develop algorithms and prove their efficacy. Topics include
propositional and predicate logic, basic proof techniques, set algebra and
Boolean algebra, recursion and induction, trees and graphs, introductory
combinatorics, and matrix algebra. The knowledge gained will be extremely
useful in upper level UNCW computer science
classes.
Text: Discrete Mathematics with Applications, by Susanna Epp, Third Edition, PWS.
Material to be Covered: Lectures/Homework Practice Quizzes
|
Chapter |
Title |
Sections |
|
Chapter 1 |
Propositional Logic |
1.1-1.5 |
|
Chapter 2 |
Predicate Logic |
2.1-2.4 |
|
Chapter 3 |
Elementary Number Theory and Methods of Proof |
3.1- 3.4, 3.6, 3.8 |
|
Chapter 4 |
Sequences and Mathematical Induction |
4.1,4.2, 4.3 |
|
Chapter 5 |
Set Theory |
5.1-5.3 |
|
Chapter 6 |
Counting |
6.1-6.7 |
|
Chapter 7 |
One-One and Onto, Cardinality |
7.1, 7.2, 7.4 |
|
Chapter 8 |
Recursion |
8.1-8.2 |
|
Chapter 9 |
O-Notation and the Efficiency of Algorithms |
9.1 - 9.5 |
|
Chapter 10 |
Relations |
10.1-10.3, 10.5 |
|
Chapter 11 |
Graphs and Trees |
11.1-11.6 |
Course Objectives: We will be studying a body of mathematical concepts
essential for the mastery of some of the higher-level computer science courses.
Our goal is to obtain a useful mastery of discrete structures and methods basic
to further work in computer science. To enhance your ability to formulate and
solve applied problems, to analyze and interpret algorithms and functions and
to use them effectively so you may enjoy the triumph of discovery that comes
from solving a problem by your own means. My goal is to help you learn how to
think about discrete mathematical models so you can do well in this course and
in your subsequent studies.
Policies:
Graded Work: There will be two 100-minute tests each counting 25%.
There will several quizzes and/or assigned homework taken up and graded. The
three lowest of these will be dropped. Homework/quiz grades will be averaged
and count 25%. The final examination (a comprehensive exam) counts 25%. The
final may also be used to replace your lowest test grade if the final is higher
than your lowest test grade.
Grading Scale:
|
90-100 A |
|
80-89.5 B |
|
70-79.5 C |
|
60-69.5 D |
When the distribution of course grades suggests a borderline grade, I may use plus or minus at my discretion.
Important Dates:
Study Strategies: We will be learning how to think about a problem and
how to apply new concepts. This process takes time and works best if spaced out
over short periods. To afford yourself the best opportunity for this process to
be successful you have to keep up on a daily basis. Cramming does not work. We
are not merely memorizing facts that can be easily applied the next morning
during an exam. Each concept must be handled in your mind, manipulated, and
finally placed in proper context with the many other concepts. You will
discover that many of these concepts are in fact identical or nearly so. Tools
we master for one application will serve us well in the next.