Engineering Mathematics 3A

MTH20007 12.5 Credit Points Hawthorn


  • One Semester or equivalent

Contact hours

  • 60 hours

On-campus unit delivery combines face-to-face and digital learning.

Aims and objectives

This unit is no longer offered from 2018 onwards.
From 2016 MTH20007 will be known as Engineering Mathematics 3A (previously known as 3M) Will replace code MTH20004
This unit aims to provide you with a coherent and balanced account of major mathematical and statistical techniques and concepts that form the basis of many engineering analysis tools. It will also introduce you to the relevant computer software that will support your engineering studies.
After successfully completing this unit, you should be able to:
1. Appreciate conceptual aspects of Fourier series expansions of periodic and periodically extended functions and apply the technique in practice. (K2, S1)
2. Demonstrate a good understanding of the Laplace transform and use it for solving linear differential equations describing motion and forces. (K2, S1)
3. Construct and interpret various graphical representations and summary statistics of datasets. (K2)
4. Apply appropriately probability concepts including unconditional and conditional probability, probability distributions, population measures of location and dispersion. (K2, S1, S2)
5. Construct and interpret quantile-quantile plots. (K2)
6. Apply the basic concepts of statistical inference, including interval estimation, sample size and hypothesis testing in various contexts. (K2, S1, S2)
7. Use concepts in correlation, regression and goodness-of-fit to analyse relationships in bivariate data. (K2, S1, S2)
8. Apply the basic principles of statistical control theory. (K2, S1)
9. Use appropriate software to assist with the above objectives. (K2, S1)
Swinburne Engineering Competencies for this Unit of Study
This Unit of Study will contribute to you attaining the following Swinburne Engineering Competencies:
K2 Maths and IT as Tools: Proficiently uses relevant mathematics and computer and information science concepts as tools.
S1 Engineering Methods: Applies engineering methods in practical applications.
S2 Problem Solving: Systematically uses engineering methods in solving complex problems.