The principal objective of the course is to provide students with a strong knowledge of numerical and statistical analysis techniques, for the modelling and solving of engineering and scientific problems. The organisation of the course is such that it is divided into two distinct components, the numerical component and the data analysis component. The Numerical component will cover topics in: Matrices, Root Finding, Optimisation, Regression, Numerical Integration,and Numerical Differentiation. The Statistics component will cover topics in: Discrete and continuous random variables, Descriptive Statistics, Probability Distributions, Confidence Intervals, Hypothesis testing, Non-Linear regression and Interpolation. The course will strongly utilise the MATLAB computer programming environment, as well as spread sheeting, for performing the numerical and statistical analysis. The course will be taught by a combination of lectures, tutorials and workshops. Students are also expected to undertake a significant amount of self-learning throughout the course. Assessments are by: Computing Laboratories, Formal Assignments, and Examinations. This course is not offered from 2017. Please seek advice from the Program Director for a suitable alternative.
10 (10)
Band 1