MATHS 770 : Advanced Numerical Analysis


2020 Semester Two (1205) (15 POINTS)

Course Prescription

Covers the use, implementation and analysis of efficient and reliable numerical algorithms for solving several classes of mathematical problems. The course assumes students have done an undergraduate course in numerical methods and can use Matlab or other high-level computational language.

Course Overview

MATHS 770 is a core applied mathematics course for the BSc(Hons), BAdvSci and PGDipSci programmes and will also be of interest to students majoring in Computer Science, Engineering Science, Physics or Statistics. It is intended for all students who need to use or learn about advanced numerical methods for computational problems in applied mathematics. After successfully completing MATHS 770 students will be well prepared to decide which advanced method to use for a specific problem and to assess if they are using the method correctly. The course has been designed so that students do not need specialist knowledge to take it, but students are expected to have a working knowledge of a high-level computer language such as Matlab or Python.​

Course Requirements

Prerequisite: B- in MATHS 270, 340 and 361

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

Learning Outcomes

By the end of this course, students will be able to:
  1. Solve examples of the types of problems covered in the course using advanced numerical methods. (Capability 1, 2, 3 and 5)
  2. Demonstrate how to check the accuracy of numerical solutions calculated using the methods. (Capability 1, 2, 3 and 4)
  3. Critique alternative methods for solving a given problem. (Capability 1, 2, 4 and 5)
  4. Demonstrate the limitations of the methods. (Capability 1, 2, 3 and 4)
  5. Demonstrate the use of the methods in a high-level software package. (Capability 1, 4 and 5)


Assessment Type Percentage Classification
Assignments 40% Group & Individual Coursework
Test 20% Individual Test
Final Exam 40% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5
Final Exam


Māori and Pasifika students are encouraged to participate in the Mathematics Tuākana Programme and use their free drop-in tutorial sessions. The programme can be accessed through the Tuākana (Science) - Maths canvas page. For further information, please visit 

Key Topics

1. Linear algebra: eigenvalue problem; factoring — QR, SVD; solving banded systems; conjugate gradient method for large sparse systems of linear algebraic equations. 
2. Approximation theory: minimax problem; continuous least squares problem.
3. Optimisation: linear least squares — full-rank and rank deficient cases; nonlinear least squares — convergence results, Gauss-Newton, Levenberg-Marquardt method; quadratic objective function with linear constraints 
4. Introduction to integral equations: statement of the different types, some results about existence; Fredholm equations — finite difference, collocation; Volterra — one-step methods
5. Nonlinear algebraic systems: quasi-Newton methods; approximation to the Jacobian; parameter continuation methods.
6. Solutions of ordinary differential equations: initial value problems; variable stepsize; stiff problems; two-point boundary value problems; shooting, collocation. 
7. Fourier transforms in one dimension: DFT versus FFT; calculating FFTs.
8. Cubic splines
9. Quadrature: globally adaptive methods.

Learning Resources

There is no required or recommended textbook for the course.

Special Requirements

No special requirements.

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.

For this course, you can expect 3 hours of lectures,  3 hours of reading and thinking about the content and 4 hours of work on assignments and/or test preparation.

Other Information

No other information.

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.


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

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:

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 (


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 04/07/2020 06:09 p.m.