Statistics and Computation for Engineering
Duration
- One semester or equivalent
Contact hours
- 60 hours face to face + Blended
On-campus unit delivery combines face-to-face and digital learning.
2023 teaching periods
| Hawthorn Higher Ed. Semester 1 |
Hawthorn Higher Ed. Semester 2 | |
|---|---|---|
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Prerequisites
or
OR both
Anti-requisite (similar in content)
Aims and objectives
This unit of study aims to provide students with mathematical knowledge and skills needed to support their concurrent and subsequent engineering and science studies.
Unit Learning Outcomes (ULO)
On successful completion of this unit students will be able to:
1. Calculate the eigenvalues and eigenvectors of 2x2 and 3x3 matrices (K2, S1)
2. Interpret the quadratic form and find its canonical form (K2, S1)
3. Execute numerical solutions of initial and boundary value problems (K2, S1)
4. Use finite difference methods to obtain numerical solutions of selected partial differential equations (K2, S1)
5. Demonstrate competence using Matlab to solve statistical and computational mathematics problems (S1)
6. Appropriately apply probability concepts including unconditional and conditional probability, probability distributions, population measures of location and dispersion to analyse data; use concepts in correlation and regression, chi-square test to analyse relationships in bivariate data (K2, S1)
7. Apply the basic concepts of statistical inference including interval estimation, sample size and hypothesis testing in various contexts (K2, S1)
Swinburne Engineering Competencies (A1-7, K1-6, S1-4): find out more about Engineering Skills and Competencies including the Engineers Australia Stage 1 Competencies.
Unit information in detail
- Teaching methods, assessment and content.
Teaching methods
Hawthorn
Type | Hours per week | Number of Weeks | Total |
Live Online Lecture | 3 | 12 | 36 |
| On Campus Class | 1 | 12 | 12 |
| On Campus Computer Lab | 1 | 12 | 12 |
| Online Directed Online Learning and Independent Learning | 1.5 | 12 | 18 |
| Unspecified Activities Independent Learning | 6 | 12 | 72 |
TOTAL | 150 hours |
Assessment
Types | Individual or Group task | Weighting | Assesses attainment of these ULOs |
Online Assignment | Individual | 10-20% | 6,7 |
Examination | Individual | 40-55% | 1,2,3,4,6,7 |
Project | Individual/Group | 15-20% | 3,4,5 |
| Test 1 | Individual | 10-15% | 1,2 |
Hurdle
As the minimum requirements of assessment to pass a unit and meet all Unit Learning Outcomes to a minimum standard, a student must achieve:
(i) an aggregate mark of 50% or more, and
(ii) at least 40% in the final exam.
Students who do not successfully achieve hurdle requirement (ii) will receive a maximum of 45% as the total mark for the unit
Content
- Matrix Analysis: eigenvalue problems, reduction to canonical form, science and engineering applications
- Initial value problems for ordinary differential equations: Taylor series and finite differences; order notation; local error estimation; Euler and Runge-Kutta methods for first order ordinary differential equations; extension to systems of equations and higher order equations
- Boundary value problems for ordinary differential equations: central difference approximation and finite difference solutions
- Finite difference solution of selected linear partial differential equations occurring in science and engineering applications
- Applied Probability and Statistics: exploratory data analysis, probability, random variables and probability distributions, hypothesis testing, correlation and regression, contingency tables
Study resources
- Reading materials.
Reading materials
A list of reading materials and/or required texts will be made available in the Unit Outline.