stm3cs computation and simulation
COMPUTATION AND SIMULATION
STM3CS
2017
Credit points: 15
Subject outline
In mathematics, one uses algebra and calculus to find 'exact' solutions to mathematical problems. In statistics, engineering, physics, and applied mathematics, when dealing with 'the real world', one encounters situations where the best one can do is to find an approximate solution to a problem. This is where computation and simulation plays a vital role. As well as appreciating the numerical methods for obtaining approximate solutions in their own right, understanding concepts such as accuracy and computational efficiency are important. Naturally, computing and simulation are carried out using software programs such as Excel spreadsheets and the technical computing languages MATLAB, Maple or R; in this subject students will gain experience using these. The specific topics studied are: nonlinear equations, interpolation, smoothing and optimization, numerical integration, pseudorandom numbers and simulation.
SchoolSchool Engineering&Mathematical Sciences
Credit points15
Subject Co-ordinatorNarwin Perkal
Available to Study Abroad StudentsYes
Subject year levelYear Level 3 - UG
Exchange StudentsYes
Subject particulars
Subject rules
Prerequisites MAT1CDE or STM2PM or MAT1CLA or STA2MD
Co-requisitesN/A
Incompatible subjects MAT3SC
Equivalent subjectsN/A
Special conditionsN/A
Graduate capabilities & intended learning outcomes
01. Apply appropriate computational methods using calculator and computer to solve mathematical and statistical problems that do not have analytic solutions
- Activities:
- Algorithms are introduced in lectures, and then implemented and explored in computer lab classes, self study exercises and assignment work.
- Related graduate capabilities and elements:
- Discipline-specific GCs(Discipline-specific GCs)
- Creative Problem-solving(Creative Problem-solving)
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
02. Determine accuracy characteristics of numerical algorithms
- Activities:
- Students discover characteristics in guided computer lab exercises and consolidate understanding in self study exercises and assignment work.
- Related graduate capabilities and elements:
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
- Discipline-specific GCs(Discipline-specific GCs)
- Creative Problem-solving(Creative Problem-solving)
03. Use appropriate mathematical language to write solutions to problems
- Activities:
- Illustrated in lectures and computer lab classes, consolidated in self study exercises and assignment work.
- Related graduate capabilities and elements:
- Writing(Writing)
- Discipline-specific GCs(Discipline-specific GCs)
04. Interpret and write explanations of the solutions to computational problems in appropriate language and write explanations of associated mathematical and statistical concepts.
- Activities:
- Illustrated in lectures and computer lab classes, consolidated in self study exercises and assignment work.
- Related graduate capabilities and elements:
- Discipline-specific GCs(Discipline-specific GCs)
- Writing(Writing)
Subject options
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Melbourne, 2017, Semester 1, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorNarwin Perkal
Class requirements
Computer Laboratory
One 2.0 hours computer laboratory per week on weekdays during the day and delivered via face-to-face.
Lecture
Two 1.0 hours lecture per week on weekdays during the day and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Examination | 60 | 04, 02, 01, 03 | |
| Four assignments (approx 350 words each) | 40 | 02, 04, 03, 01 |