60 hours

Hawthorn, Sarawak

Credit Points: 12.5 Credit Points

Related Course/s:

Aims & Objectives:

• Solve eigenvalue problems
• Use eigenvalue techniques to solve differential equations
• Solve first order and second order initial value problems using Euler and Runge-Kutta methods.
• Apply the finite difference method to solve boundary value problems.
• Produce and interpret various graphical representations and summary statistics of datasets.
• Understand and apply basic concepts of probability, including calculating and interpreting unconditional and conditional probabilities.
• Recognise, use and appropriately apply general and standard discrete and continuous probability distributions.
• Calculate and interpret measures of location and dispersion for populations.
• Understand, create and interpret quantile-quantile plots.
• Understand the basic concepts of statistical inference, including interval estimation, sample size and hypothesis testing.
• Apply the basic concepts of statistical inference in various contexts.
• Understand and apply concepts in correlation and regression, including fitting, interpreting and applying simple linear regression models.
• Understand twoway contingency tables and carry out goodness of fit tests on such tables.
• Understand and apply the principles of basic extreme value theory.
• Use a particular kind of graphics calculator and a particular statistics package to assist with the above objectives

Teaching Methods:

Assessment:

Generic Skills Outcomes:

• Ability to apply knowledge of basic science and engineering fundamentals
• Ability to communicate effectively, not only with engineers but also with the community at large
• Ability to undertake problem identification, formulation and solution

• Ability to apply knowledge of basic science and engineering fundamentals;
• In-depth technical competence in at least one engineering discipline;
• Expectation of the need to undertake lifelong learning, and capacity to do so.

Content:

• Numerical Solution of Differential Equations (25%): Ordinary differential equations: Initial value and boundary value problems, finite difference methods, and engineering application. 
• Matrix Analysis (25%) The eigenvalue problem, numerical methods, reductions to canonical form and engineering application
• Applied Probability and Statistics (50%): Exploratory data analysis, probability, random variables and probability distributions, important practical distributions, quantile-quantile plots, sampling distributions, estimation and statistical inference, correlation and regression, contingency tables and goodness of fit tests, extreme value distributions with application to hydrology.

Note: A Statistics package and a Mathematics package will be used in this unit. Students will be expected to have access to a particular kind of graphics calculator.

Reading Materials:

Notes will be provided via Blackboard or the Swinburne Bookshop.

References: