PROBABILITY MODELS
STM2PM
2018
Credit points: 15
Subject outline
The analysis of scientific, engineering and economic data makes extensive use of probability models. This subject describes the most basic of these models and their properties. Specific topics covered in this subject include a wide range of discrete and continuous univariate distributions; joint distributions; conditional expectation; mean and variance of linear combinations of random variables; Chebyshev's inequality; moment generating functions; the law of large numbers; the Central Limit Theorem. To help students with little or no previous knowledge of calculus, the equivalent of one lecture per week consists of relevant mathematical topics to support the other content.
School: School Engineering&Mathematical Sciences
Credit points: 15
Subject Co-ordinator: Marcel Jackson
Available to Study Abroad Students: Yes
Subject year level: Year Level 2 - UG
Exchange Students: Yes
Subject particulars
Subject rules
Prerequisites: (MAT1CDE and MAT1NLA) or MAT1CLA or STA1SS or STA1LS or STA1PSY
Co-requisites: N/A
Incompatible subjects: STA2MD AND STA2MDA
Equivalent subjects: N/A
Special conditions: N/A
Graduate capabilities & intended learning outcomes
01. Model and solve problems when randomness is involved
- Activities:
- Modelled in lectures, and practised in tutorials
- Related graduate capabilities and elements:
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
02. Compute/derive mathematical calculations to investigate numerical properties of probability models
- Activities:
- Modelled in lectures, and practised in tutorials
- Related graduate capabilities and elements:
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
03. Derive some basic probability results in selected areas of application
- Activities:
- Modelled in lectures, and practised in tutorials
- Related graduate capabilities and elements:
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
04. Defend or question the validity of different probability models
- Activities:
- Modelled in lectures, and practised in tutorials
- Related graduate capabilities and elements:
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
05. Present clear, well structured explanations of numerical results including the appropriate use of statistical and mathematical vocabulary
- Activities:
- Modelled in lectures, and practised in tutorials and on formative assignments, with particular emphasis on the work students complete at home with time to proof-read
- Related graduate capabilities and elements:
- Discipline -Specific Knowledge and Skills(Discipline-Specific Knowledge and Skills)
Melbourne, 2018, Semester 2, Day
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Enrolment information:
Subject Instance Co-ordinator: Marcel Jackson
Class requirements
Lecture
Three 1.0 hours lecture per week on weekdays during the day and delivered via face-to-face.
Tutorial
One 1.0 hours tutorial per week on weekdays during the day and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| 2.5 hour Exam | 70 | 05, 03, 02, 04 | |
| 5 assignments (1500 words equivalent total) | 30 | 04, 01, 03, 05, 02 |