MATH36022 Online Resources (2019)
See the course syllabus and see how this course fits in the Numerical Analysis Pathway.
The mid-term test has now taken place. Scripts can be collected from reception in the Alan Turing Building.
Thank you for filling in Week 3 feedback forms. My response to your comments is here.
Lecturer: Dr. Catherine Powell
Office: 1.124, Alan Turing Building. Office Hours: Monday 3-4pm.
Lectures: Tuesday 10am (Kilburn, Theatre 1.5), Tuesday 11am (Schuster, Blackett) Example Class: Monday, 10am (University Place, 4.206).
You will need to use MATLAB occasionally and should know how to set up vectors, perform mathematical operations on vectors, write simple programmes and plot functions. If you are not confident with MATLAB don't panic. Examples will be given on handouts. Many useful MATLAB resources and tutorials can be found on the web, including, HERE.
Occasionally, we will need results from analysis from earlier courses. These results are summarised in the above document. Students are expected to know these results and should be prepared to use them during the course wherever necessary.
Handouts & Lecture Notes
Online materials (handouts), to read in between lectures, will be provided below. If you prefer paper copies, let me know. A full set of lecture notes will be provided on Blackboard . I recommend reading these only after we've discussed the material in class. Students are expected to take their own notes in the lectures. Anyone with special support needs or special circumstances preventing them from attending lectures should contact me to make arrangements.
Acknowledgement: The notes have been adapted from notes written by Nick Higham for an older version of this course.
Section 1: Approximation of functions
We have now finished this section. Full lecture notes for Section 1 are available on Blackboard.
Section 2: Quadrature
We have now finished this section. Full lecture notes for Section 2 are available on Blackboard.
Section 3: Numerical methods for solving ODEs
Full lecture notes for Section 3 are available on Blackboard.
- Lecture 15: Example IVPs for ODEs
- Lecture 16: Euler's method
Matlab files: euler.m and my_f.m
- Lecture 17: Introduction to RK methods (the improved Euler method)
- Lecture 18: m-stage Runge Kutta methods
- Lecture 20: Euler-Trapezium Predictor-Corrector method
Short quizzes from Examples Classes:
Of all the text books that appear on the official reading list, the one I recommend most is:
- Endre Suli and David F. Mayers. An Introduction to Numerical Analysis. Cambridge University Press, Cambridge, UK, 2003
The mid-term test has now taken place. This is worth 20% of the overall mark for the course.
Exam resources and feedback
Tutorials will provide an opportunity for students' work to be
discussed and provide feedback on their understanding. Coursework or
in-class tests (where applicable) also provide an opportunity for
students to receive feedback. Students can also get feedback on
their understanding directly from the lecturer, for example during
the lecturer's office hour.
Recent past exam papers are avaliable from main School of Mathematics website. Note - I did not teach the course in 2018.
Feedback report on the May 2017 exam.
Feedback report on the June 2016 exam.
Feedback report on the May 2015 exam.