Note: This is an archived Handbook entry from 2009. Search for this in the current handbook
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2009:Semester 1, - Taught on campus.
Lectures, computer laboratory classes and project work.
Timetable can be viewed here. For information about these dates, click here.
|Time Commitment:||Contact Hours: 24 one-hour lectures (two per week), 12 one-hour computer laboratory classes (one per week) and 60 hours of project work |
Total Time Commitment: 120 hours total time commitment.
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|Recommended Background Knowledge:||None|
|Non Allowed Subjects:||None|
|Core Participation Requirements:||It is University policy to take all reasonable steps to minimise the impact of disability upon academic study and reasonable steps will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact upon their active and safe participation in a subject are encouraged to discuss this with the relevant subject coordinator and the Disability Liaison Unit.|
CoordinatorDr Steven Lyle Carnie
This subject introduces the underlying basis for numerical techniques to solve a variety of problems; and the role of various kinds of numerical error and how algorithms are designed to minimise this error; and develops basic algorithms in the areas of root-finding, linear systems, interpolation, quadrature and solution of differential equations. Students should acquire skills in implementing the above algorithms in well-constructed computer programs and interpreting the results obtained from the programs. This subject demonstrates the difficulties and possible pitfalls in numerical computation. It also shows where to find sources of reliable numerical software.
Topics include errors, roundoff, truncation error and stability; root-finding, iteration, bisection, Newton's method and secant method; linear systems, Gauss elimination, pivoting, LU factorisation, tridiagonal systems, condition number; interpolation, polynomial and spline; data fitting and least squares methods; quadrature, Newton-Cotes, Gaussian quadrature, adaptive quadrature and improper integrals; and differential equations and initial value problems: Euler, Runge-Kutta, predictor-corrector and stiff problems.
Computational assignments of up to 75 pages in total due during the semester (50%); a 2-hour written examination in the examination period (50%).
|Breadth Options:|| |
This subject potentially can be taken as a breadth subject component for the following courses:
You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
|Notes:||This subject is available for science credit to students enrolled in the BSc (pre-2008 degree only), BASc or a combined BSc course.|
Mathematics && Statistics Major |
Mathematics and Statistics (Applied Mathematics specialisation)
Mathematics and Statistics (Discrete Mathematics specialisation)
Mathematics and Statistics (Financial Mathematics specialisation)
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