MATHS 326 : Combinatorics

Science

2020 Semester One (1203) (15 POINTS)

Course Prescription

Combinatorics is a branch of mathematics that studies collections of objects that satisfy specified criteria. An important part of combinatorics is graph theory, which is now connected to other disciplines including bioinformatics, electrical engineering, molecular chemistry and social science. The use of combinatorics in solving counting and construction problems is covered using topics that include algorithmic graph theory, codes and incidence structures, and combinatorial complexity.

Course Overview

This course is intended for students who have enjoyed basic combinatorics and discrete mathematics presented in MATHS 255 and COMPSCI 225. It expands on the concepts seen in those classes: students are introduced to graph colourings, planarity, etc. Several major theorems in the area are covered: the Five-Colour Theorem, Euler's Formula, Hall's Marriage Theorem. The syllabus also includes incidence structures such as designs, projective planes. To show applicability of combinatorics to real-life problems we consider prefix codes and universal compression codes with applications to computer science, and simple games which have applications to economics and political science. After successfully completing this course on combinatorics, students will have a solid foundation in this field of growing importance, will be familiar with some important applications of combinatorics. Students will also be well prepared for further graduate courses on the topic, such as MATHS 715 or MATHS 782.

Course Requirements

Prerequisite: MATHS 254 or 255, or COMPSCI 225 and a B+ or higher in MATHS 208, or COMPSCI 225 and MATHS 250

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Capability 5: Independence and Integrity
Capability 6: Social and Environmental Responsibilities
Graduate Profile: Bachelor of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Display a high level of knowledge about combinatorial structures and their properties. (Capability 1 and 2)
  2. Understand the applications and connections to other disciplines. (Capability 1 and 3)
  3. Understand the nature of proof and precision in mathematics, present both formally and informally arguments in both verbal and written form. (Capability 2, 4 and 5)
  4. Display ability to model and solve problems. (Capability 2 and 3)
  5. Engage in critical interactions. (Capability 3, 4 and 6)

Assessments

Assessment Type Percentage Classification
Final Exam 50% Individual Examination
Test 20% Individual Test
Assignments 20% Individual Coursework
Quizzes 5% Group & Individual Coursework
Workshops 5% Group Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4 5
Final Exam
Test
Assignments
Quizzes
Workshops

You must achieve at least 35% in the final exam in order to pass the course

Key Topics

  •  Graph colourings
  • Graph algorithms
  • Incidence structures
  • Compression codes
  • Simple games

Learning Resources

There is no text book, but a set of notes will be made available on Canvas. There is also a broad collection of books in the library on these topics, as well as plenty of online resources.

Special Requirements

N/A

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

Other Information

This course uses a Team Based Learning approach. At the beginning of the course, students are assigned to teams of approximately five students in each team. After a preliminary topic devoted to revision of the basics, the course is divided into five main topics. Each topic has the same structure: preliminary reading, available in advance, followed by a readiness assurance test (RAT). This is a multi-choice quiz based on the reading, and it has an individual and a team components.  Near the end of each topic, there is a team task, where students are set a problem to solve as a group during class.

Digital Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Copyright

The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website at http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page: https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter (https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html).

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.

Published on 11/01/2020 03:12 p.m.