Overview
MATH2089 is a Level II course which is available only to students for whom it is specifically required as part of their program. See the聽course overview聽below.
Units of credit:听6
Prerequisites:聽MATH1231 or MATH1241 or MATH1251 or DPST1014
Exclusions:聽BEES2041, CVEN2002, CVEN2702, MATH2099, MATH2301, MATH2801, MATH2859, MATH2901, ECON3209
Cycle of offering:聽Term 1 & 2聽
Graduate attributes:聽The course will enhance your research, inquiry and analytical thinking abilities.
More information:聽The course outline contains information about course objectives, assessment, course materials and the syllabus.
Important additional information as of 2023
UNSW Plagiarism Policy
The University requires all students to be aware of its聽.
For courses convened by the聽School of Mathematics and Statistics no assistance using generative AI software is allowed unless specifically referred to in the individual assessment tasks.
If its use is detected in the no assistance case, it will be regarded as serious academic misconduct and subject to the standard penalties, which may include 00FL, suspension and exclusion.
罢丑别听聽contains up-to-date timetabling information.
If you are currently enrolled in MATH2089, you can log into聽聽for this course.
Course description
This course gives an introduction to numerical methods and statistics essential in a wide range of engineering disciplines.
Numerical methods:聽Computing with real numbers. Numerical differentiation, integration, interpolation and curve fitting (regression analysis). Solution of linear and nonlinear algebraic equations. Matrix operations and applications to solution of systems of linear equations, elimination and tri-diagonal matrix algorithms. Introduction to numerical solution of ordinary and partial differential equations.
Statistics:聽Exploratory data analysis. Probability and distribution theory including the Binomial, Poisson and Normal distributions. Large sample theory including the Central Limit Theorem. Elements of statistical inference including estimation, confidence intervals and hypothesis testing. One sample and two-sample t-tests and F-tests. Simple and multiple linear regression and analysis of variance. Statistical quality control.
In each component, applications will be drawn from a variety of engineering disciplines. Matlab will be used extensively as a practical tool for both numerical and statistical computations and to illustrate theoretical concepts.