stm2pm probability models
PROBABILITY MODELS
STM2PM
2017
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.
SchoolSchool Engineering&Mathematical Sciences
Credit points15
Subject Co-ordinatorMarcel Jackson
Available to Study Abroad StudentsYes
Subject year levelYear Level 2 - UG
Exchange StudentsYes
Subject particulars
Subject rules
Prerequisites (MAT1CDE and MAT1NLA) or MAT1CLA or STA1SS or STA1LS or STA1PSY
Co-requisitesN/A
Incompatible subjects STA2MD AND STA2MDA
Equivalent subjectsN/A
Special conditionsN/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:
- Inquiry/ Research(Inquiry/ Research)
- Creative Problem-solving(Creative Problem-solving)
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
- Critical Thinking(Critical Thinking)
- Discipline-specific GCs(Discipline-specific GCs)
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:
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
- Discipline-specific GCs(Discipline-specific GCs)
- Creative Problem-solving(Creative Problem-solving)
- Critical Thinking(Critical Thinking)
- Inquiry/ Research(Inquiry/ Research)
03. Derive some basic probability results in selected areas of application
- Activities:
- Modelled in lectures, and practised in tutorials
- Related graduate capabilities and elements:
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
- Critical Thinking(Critical Thinking)
- Discipline-specific GCs(Discipline-specific GCs)
04. Defend or question the validity of different probability models
- Activities:
- Modelled in lectures, and practised in tutorials
- Related graduate capabilities and elements:
- Creative Problem-solving(Creative Problem-solving)
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
- Critical Thinking(Critical Thinking)
- Discipline-specific GCs(Discipline-specific GCs)
- Writing(Writing)
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:
- Writing(Writing)
- Quantitative Literacy/ Numeracy(Quantitative Literacy/ Numeracy)
Subject options
Select to view your study options…
Melbourne, 2017, Semester 2, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorMarcel 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 | 30 | 04, 01, 03, 05, 02 |