Docsity
Docsity

Prepare for your exams
Prepare for your exams

Study with the several resources on Docsity


Earn points to download
Earn points to download

Earn points by helping other students or get them with a premium plan


Guidelines and tips
Guidelines and tips

Comments - Based on Dosey and Spence | MATH 206, Study notes of Discrete Mathematics

Material Type: Notes; Professor: Stephen; Class: Introductory Discrete Mathematics; Subject: MATHEMATICAL SCIENCES; University: Northern Illinois University; Term: Unknown 1989;

Typology: Study notes

Pre 2010

Uploaded on 08/18/2009

koofers-user-lbu
koofers-user-lbu 🇺🇸

10 documents

1 / 2

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
Comments on MATH 206
JB (Buck) Stephen
based on Dosey/Spence 5th Ed.
MATH 206 is now required in various emphases in the CSCI program, and the majority of the
students taking MATH 206 are computer science majors: however, a typical class may also contain
majors in the various social sciences.
The underlying mathematical theme of the of the course delivery should address the following
goals - which also include the general education goals of the course:
1. Develop a basic understanding and ability to apply combinatorial models for structure (equiv-
alence relations, partial orders, graphical representation).
2. Develop an appreciation of proceduralism and an ability to structure an approach to various
types of problems. In particular, a distinction should be made between ad hoc methodology
and approaches applicable only to special cases, and generalizable techniques.
For example, when discussing the Euclidean algorithm for finding the greatest common divisor,
one should point out
(a) IF we can factor the two integers involved, then the gcd can be easily obtained, BUT
facoring is difficult.
(b) The Euclidean algorithm is applicable whether or not we have the factors of the integers,
and is less complex than finding the factors.
3. Develop a basic understanding of computational complexity. This should be reinforced through-
out the course and efficiency should be discussed.
For example: in section 1.4 various techniques for evaluating polynomials are discussed. At this
time discuss that computers perform addition much faster than multiplication and compare the
number of multiplications involved in evaluating the polinomials on both sides of an equation
such as the one preceding Horner’s method on pg 27.
4. An understanding of the halting problem - that is, how do we know a process ends. For instance,
the Euclidean algorithm ends eventually because the remainders decrease at every step and
are bounded below by 0. Contrast the with long division, which may never end.
With reference to the Euclidean algorithm, I note that this is another chance to discuss com-
plexity, in particular, given integers aand bwe do not have an effective way to predict the
actual number of steps we have to take to get the gcd, even though it is bounded by the largest
integer.
5. Develop the basic counting skills needed to further investigate combinatorial problems and
complexity.
6. Develop an understanding of the basics of formal logic.
7. Provide an introduction to matrices, their uses as data structures, and their use in representing
graphs and enumerating paths.
1
pf2

Partial preview of the text

Download Comments - Based on Dosey and Spence | MATH 206 and more Study notes Discrete Mathematics in PDF only on Docsity!

Comments on MATH 206 JB (Buck) Stephen based on Dosey/Spence 5th Ed. MATH 206 is now required in various emphases in the CSCI program, and the majority of the students taking MATH 206 are computer science majors: however, a typical class may also contain majors in the various social sciences. The underlying mathematical theme of the of the course delivery should address the following goals - which also include the general education goals of the course:

  1. Develop a basic understanding and ability to apply combinatorial models for structure (equiv- alence relations, partial orders, graphical representation).
  2. Develop an appreciation of proceduralism and an ability to structure an approach to various types of problems. In particular, a distinction should be made between ad hoc methodology and approaches applicable only to special cases, and generalizable techniques. For example, when discussing the Euclidean algorithm for finding the greatest common divisor, one should point out

(a) IF we can factor the two integers involved, then the gcd can be easily obtained, BUT facoring is difficult. (b) The Euclidean algorithm is applicable whether or not we have the factors of the integers, and is less complex than finding the factors.

  1. Develop a basic understanding of computational complexity. This should be reinforced through- out the course and efficiency should be discussed. For example: in section 1.4 various techniques for evaluating polynomials are discussed. At this time discuss that computers perform addition much faster than multiplication and compare the number of multiplications involved in evaluating the polinomials on both sides of an equation such as the one preceding Horner’s method on pg 27.
  2. An understanding of the halting problem - that is, how do we know a process ends. For instance, the Euclidean algorithm ends eventually because the remainders decrease at every step and are bounded below by 0. Contrast the with long division, which may never end. With reference to the Euclidean algorithm, I note that this is another chance to discuss com- plexity, in particular, given integers a and b we do not have an effective way to predict the actual number of steps we have to take to get the gcd, even though it is bounded by the largest integer.
  3. Develop the basic counting skills needed to further investigate combinatorial problems and complexity.
  4. Develop an understanding of the basics of formal logic.
  5. Provide an introduction to matrices, their uses as data structures, and their use in representing graphs and enumerating paths.
  1. Develop an appreciation, and an ability to use and analize graphs and trees as abstract objects, and as data structures. The chapters on graphs and trees contain several algorithms of importance both in their utility and as excellent examples of the process involved in developing algorithms. These algorithms should be discussed at length; including, the development of the underlying recursive ideas, the formation of a flow chart descrition of the process, the necessity and development of notation, and the final form of the algorithm.