PROBABILITY MODELS

STM2PM

2020

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.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorNadiya Kosytsina

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 2 - UG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

PrerequisitesSTA1SS OR MAT1CLA OR STA1PSY OR STA1LS OR (MAT1CDE AND MAT1NLA)

Co-requisitesN/A

Incompatible subjectsSTA2MD

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Career Ready

Career-focusedNo

Work-based learningNo

Self sourced or Uni sourcedN/A

Entire subject or partial subjectN/A

Total hours/days requiredN/A

Location of WBL activity (region)N/A

WBL addtional requirementsN/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

DISCIPLINE KNOWLEDGE AND SKILLS

Intended Learning Outcomes

01. Model and solve problems when randomness is involved
02. Compute/derive mathematical calculations to investigate numerical properties of probability models
03. Derive some basic probability results in selected areas of application
04. Defend or question the validity of different probability models
05. Present clear, well structured explanations of numerical results including the appropriate use of statistical and mathematical vocabulary

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2020, Semester 2, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorNadiya Kosytsina

Class requirements

Lecture Week: 0 - 0
Three 1.00 h lecture per week on weekdays during the day from week 0 to week 0 and delivered via face-to-face.

Tutorial Week: 0 - 0
One 1.00 h tutorial per week on weekdays during the day from week 0 to week 0 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*
2 hour Exam (Equivalent to 3000 words)N/AN/AN/ANo70 SILO2, SILO3, SILO4, SILO5
5 assignments (1500 words equivalent total)N/AN/AN/ANo30 SILO1, SILO2, SILO3, SILO4, SILO5