ROCHESTER INSTITUTE OF TECHNOLOGY COURSE OUTLINE FORM COLLEGE OF SCIENCE. School of Mathematical Sciences

Similar documents
Probability and Game Theory Course Syllabus

STA 225: Introductory Statistics (CT)

Self Study Report Computer Science

16 WEEKS STUDY PLAN FOR BS(IT)2 nd Semester

WSU Five-Year Program Review Self-Study Cover Page

Proof Theory for Syntacticians

Mathematics. Mathematics

Statewide Framework Document for:

Probability and Statistics Curriculum Pacing Guide

Objectives. Chapter 2: The Representation of Knowledge. Expert Systems: Principles and Programming, Fourth Edition

Mathematics Assessment Plan

MTH 215: Introduction to Linear Algebra

Radius STEM Readiness TM

AGS THE GREAT REVIEW GAME FOR PRE-ALGEBRA (CD) CORRELATED TO CALIFORNIA CONTENT STANDARDS

Honors Mathematics. Introduction and Definition of Honors Mathematics

On the Polynomial Degree of Minterm-Cyclic Functions

UNIT ONE Tools of Algebra

Artificial Neural Networks written examination

University of Groningen. Systemen, planning, netwerken Bosman, Aart

Revised on Common Course Number Data Sheet 221 Course Identification. Campus Course Attribute. Prerequisite Text Min.

CAAP. Content Analysis Report. Sample College. Institution Code: 9011 Institution Type: 4-Year Subgroup: none Test Date: Spring 2011

Level 6. Higher Education Funding Council for England (HEFCE) Fee for 2017/18 is 9,250*

Spring 2016 Stony Brook University Instructor: Dr. Paul Fodor

Grade 6: Correlated to AGS Basic Math Skills

Given a directed graph G =(N A), where N is a set of m nodes and A. destination node, implying a direction for ow to follow. Arcs have limitations

Mathematics subject curriculum

A Version Space Approach to Learning Context-free Grammars

Lecture 1: Basic Concepts of Machine Learning

Cal s Dinner Card Deals

We are strong in research and particularly noted in software engineering, information security and privacy, and humane gaming.

S T A T 251 C o u r s e S y l l a b u s I n t r o d u c t i o n t o p r o b a b i l i t y

A R "! I,,, !~ii ii! A ow ' r.-ii ' i ' JA' V5, 9. MiN, ;

Language properties and Grammar of Parallel and Series Parallel Languages

Math 098 Intermediate Algebra Spring 2018

Introduction to HPSG. Introduction. Historical Overview. The HPSG architecture. Signature. Linguistic Objects. Descriptions.

Timeline. Recommendations

Theory of Probability

GACE Computer Science Assessment Test at a Glance

Learning Disability Functional Capacity Evaluation. Dear Doctor,

Diagnostic Test. Middle School Mathematics

THE UNIVERSITY OF SYDNEY Semester 2, Information Sheet for MATH2068/2988 Number Theory and Cryptography

PH.D. IN COMPUTER SCIENCE PROGRAM (POST M.S.)

Statistics and Data Analytics Minor

Using the Attribute Hierarchy Method to Make Diagnostic Inferences about Examinees Cognitive Skills in Algebra on the SAT

Computer Science 141: Computing Hardware Course Information Fall 2012

Math 181, Calculus I

Lahore University of Management Sciences. FINN 321 Econometrics Fall Semester 2017

Technical Manual Supplement

ENME 605 Advanced Control Systems, Fall 2015 Department of Mechanical Engineering

Instructor: Matthew Wickes Kilgore Office: ES 310

South Carolina English Language Arts

Page 1 of 11. Curriculum Map: Grade 4 Math Course: Math 4 Sub-topic: General. Grade(s): None specified

Dublin City Schools Mathematics Graded Course of Study GRADE 4

CS 1103 Computer Science I Honors. Fall Instructor Muller. Syllabus

This Performance Standards include four major components. They are

Classifying combinations: Do students distinguish between different types of combination problems?

PELLISSIPPI STATE TECHNICAL COMMUNITY COLLEGE MASTER SYLLABUS APPLIED STATICS MET 1040

Python Machine Learning

Montana Content Standards for Mathematics Grade 3. Montana Content Standards for Mathematical Practices and Mathematics Content Adopted November 2011

4.0 CAPACITY AND UTILIZATION


AN EXAMPLE OF THE GOMORY CUTTING PLANE ALGORITHM. max z = 3x 1 + 4x 2. 3x 1 x x x x N 2

Lecture Notes on Mathematical Olympiad Courses

Rule Learning With Negation: Issues Regarding Effectiveness

DOCTOR OF PHILOSOPHY IN ARCHITECTURE

Focus of the Unit: Much of this unit focuses on extending previous skills of multiplication and division to multi-digit whole numbers.

CS 101 Computer Science I Fall Instructor Muller. Syllabus

MSc Education and Training for Development

Disciplinary Literacy in Science

4. Long title: Emerging Technologies for Gaming, Animation, and Simulation

On-Line Data Analytics

EGRHS Course Fair. Science & Math AP & IB Courses

ME 4495 Computational Heat Transfer and Fluid Flow M,W 4:00 5:15 (Eng 177)

Software Maintenance

Mathematics Program Assessment Plan

Algebra 1, Quarter 3, Unit 3.1. Line of Best Fit. Overview

Chapter 2 Rule Learning in a Nutshell

MBA 510: Critical Thinking for Managers

Version Space. Term 2012/2013 LSI - FIB. Javier Béjar cbea (LSI - FIB) Version Space Term 2012/ / 18

Numeracy Medium term plan: Summer Term Level 2C/2B Year 2 Level 2A/3C

AP Calculus AB. Nevada Academic Standards that are assessable at the local level only.

OPTIMIZATINON OF TRAINING SETS FOR HEBBIAN-LEARNING- BASED CLASSIFIERS

Beyond the Pipeline: Discrete Optimization in NLP

B.S/M.A in Mathematics

Grammars & Parsing, Part 1:

Heritage Korean Stage 6 Syllabus Preliminary and HSC Courses

Julia Smith. Effective Classroom Approaches to.

TABE 9&10. Revised 8/2013- with reference to College and Career Readiness Standards

Note: Principal version Modification Amendment Modification Amendment Modification Complete version from 1 October 2014

Lecture 1: Machine Learning Basics

Tabular and Textual Methods for Selecting Objects from a Group

Syllabus ENGR 190 Introductory Calculus (QR)

Content Language Objectives (CLOs) August 2012, H. Butts & G. De Anda

Rule Learning with Negation: Issues Regarding Effectiveness

Writing Research Articles

TabletClass Math Geometry Course Guidebook

CELTA. Syllabus and Assessment Guidelines. Third Edition. University of Cambridge ESOL Examinations 1 Hills Road Cambridge CB1 2EU United Kingdom

MASTER OF ARCHITECTURE

PROGRAMME SPECIFICATION UWE UWE. Taught course. JACS code. Ongoing

Degree Qualification Profiles Intellectual Skills

Transcription:

! ROCHESTER INSTITUTE OF TECHNOLOGY COURSE OUTLINE FORM COLLEGE OF SCIENCE School of Mathematical Sciences New Revised COURSE: COS-MATH-131 Discrete Mathematics 1.0 Course designations and approvals: Required Course Approvals: Approval Approval Request Date Grant Date Academic Unit Curriculum Committee 11-08-10 11-08-10 College Curriculum Committee 11-10-10 11-17-10 Optional Course Designations: Yes No General Education Writing Intensive Honors Approval Request Date Approval Grant Date 2.0 Course information: Course Title: Discrete Mathematics Credit Hours: 4 Prerequisite(s): COS-MATH-101 or equivalent Co-requisite(s): None Course proposed by: School of Mathematical Sciences Effective date: Fall 2013 Contact Hours Maximum Students/section Classroom 4 35 Lab Workshop Other (specify) 2.1 Course conversion designation: (Please check which applies to this course) Semester Equivalent (SE) to: Semester Replacement (SR) to: 1016-205, 1016-206 New 2.2 Semester(s) offered: Fall Spring Summer Offered every other year only Other Page 1 of??

2.3 Student requirements: Students required to take this course: (by program and year, as appropriate) First-year Game Design and Development, and Information Technology majors Students who might elect to take the course: Students seeking to strengthen their technical background in mathematics 3.0 Goals of the course: (including rationale for the course, when appropriate) 3.1 To provide knowledge of the mathematical concepts needed for computer technology. 3.2 To discuss the many applications of discrete mathematics to computer science and computer information systems. 3.3 To stress the applications of theorem results in information technology and game design and development. 4.0 Course description: (as it will appear in the RIT Catalog, including pre- and co-requisites, semesters offered) COS-MATH-131 Discrete Mathematics This course in an introduction to the topics of discrete mathematics, including number systems, sets and logic, relations, combinatorial methods, graph theory, regular sets, vectors, and matrices. (COS-MATH-101 or equivalent) Class 4, Credit 4 (F, S) 5.0 Possible resources: (texts, references, computer packages, etc.) 5.1 Molluzzo and Buckley, A First Course in Discrete Mathematics, Waveland Press, Long Grove, IL. 5.2 Siegel, Schaum s Outline of Discrete Mathematics, McGraw-Hill, Columbus, OH. 5.3 Wallis, W.D., A Beginner s Guide to Discrete Mathematics, Birkhauser, New York, NY. 6.0 Topics: (outline) Topics with an asterisk(*) are at the instructor s discretion, as time permits 6.1 Number Systems 6.1.1 The binary, octal, and hexadecimal systems 6.1.2 The integers 6.1.3 Modular arithmetic 6.2 Sets 6.2.1 Sets, subsets, power sets, and Venn diagrams 6.2.2 Set representations 6.2.3 Intersections, unions, and complement 6.3 Logic 6.3.1 Conjunction, disjunction, and negation 6.3.2 Tautologies and contradictions 6.3.3 Logical implication and decision tables 6.3.4 First order quantifiers Page 2 of??

6.3.5 Proof techniques 6.4 Functions 6.4.1 Introduction to relations through the Cartesian product of sets 6.4.2 Partial orders and equivalence relations 6.4.3 Operations on functions; one-to-one, onto, and inverse functions 6.4.4 Recursively defined functions 6.4.5 Mathematical induction 6.5 Counting 6.5.1 Permutations and combinations 6.5.2 Binomial coefficients 6.5.3 Pigeonhole principle 6.6 Graph Theory 6.6.1 Examples of graphs, including K n, C n, trees, directed graphs, and weighted graphs 6.6.2 Isomorphic graphs 6.6.3 Graph traversal problems, including the traveling salesman problem 6.6.4 Shortest paths and Dijkstra s algorithm 6.7 Arrays 6.7.1 Vectors and matrices 6.7.2 Matrices associated with graphs 6.7.3 Matrix operations 6.7.4 Bit clearing, bit masking 6.8 Regular Sets 6.8.1 Regular expressions 6.8.2 Linear grammars 6.8.3 Finite state automata 6.8.4 Equivalence of regular expressions, linear grammars, and finite state automata 7.0 Intended learning outcomes and associated assessment methods of those outcomes: Assessment Methods Learning Outcomes 7.1 Use binary, octal, and hexidecimal representations of natural numbers 7.2 Use notation of set theory and logic and elementary proof techniques in written communication Page 3 of??

Assessment Methods Learning Outcomes 7.3 Use language of set theory to analyze functions, relations, graphs, and inverse functions 7.4 Write proofs using mathematical induction 7.5 Solve elementary combinatorial problems using the rules of product and sum, the binomial theorem, and binomial coefficients 7.6 Multiply matrices, and perform Boolean operations on matrices 7.7 Identify classes of graphs and describe their properties 7.8 Apply basic algorithms of graph theory 7.9 Examine operation of finite state automata and regular expressions 8.0 Program goals supported by this course: 8.1 To develop an understanding of the mathematical framework that supports engineering, science, and mathematics. 8.2 To develop critical and analytical thinking. 8.3 To develop an appropriate level of mathematical literacy and competency. 8.4 To provide an acquaintance with mathematical notation used to express physical and natural laws. 9.0 General education learning outcomes and/or goals supported by this course: Assessment Methods General Education Learning Outcomes 9.1 Communication Express themselves effectively in common college-level written forms using standard American English Revise and improve written and visual content Page 4 of??

Assessment Methods General Education Learning Outcomes Express themselves effectively in presentations, either in spoken standard American English or sign language (American Sign Language or English-based Signing) Comprehend information accessed through reading and discussion 9.2 Intellectual Inquiry Review, assess, and draw conclusions about hypotheses and theories Analyze arguments, in relation to their premises, assumptions, contexts, and conclusions Construct logical and reasonable arguments that include anticipation of counterarguments Use relevant evidence gathered through accepted scholarly methods and properly acknowledge sources of information 9.3 Ethical, Social and Global Awareness Analyze similarities and differences in human experiences and consequent perspectives Examine connections among the world s populations Identify contemporary ethical questions and relevant stakeholder positions 9.4 Scientific, Mathematical and Technological Literacy Explain basic principles and concepts of one of the natural sciences Apply methods of scientific inquiry and problem solving to contemporary issues Comprehend and evaluate mathematical and statistical information Perform college-level mathematical operations on quantitative data Describe the potential and the limitations of technology Use appropriate technology to achieve desired outcomes 9.5 Creativity, Innovation and Artistic Literacy Demonstrate creative/innovative approaches to coursebased assignments or projects Interpret and evaluate artistic expression considering the cultural context in which it was created Page 5 of??

10.0 Other relevant information: (such as special classroom, studio, or lab needs, special scheduling, media requirements, etc.) None Page 6 of??