APPLIED STATISTICS
STA3AS
2021
Credit points: 15
Subject outline
The purpose of STA3AS is to equip graduates with an in depth understanding of modern statistical methods in the following three key topics: 1. Sample surveys with an emphasis on simple random sampling and stratified random sampling. 2. Multivariate analysis with an emphasis on inference for the multivariate mean, checking for underlying multivariate normality, principal component analysis and discriminant analysis. This topic includes an introduction/review of common linear algebra results. 3. Time series analysis with an introduction into the theoretical foundation of Box-Jenkins univariate time series models which form a basis for empirical work with time series data. The software package used in this subject is R.
SchoolEngineering and Mathematical Sciences
Credit points15
Subject Co-ordinatorPaul Kabaila
Available to Study Abroad/Exchange StudentsYes
Subject year levelYear Level 3 - UG
Available as ElectiveNo
Learning ActivitiesN/A
Capstone subjectNo
Subject particulars
Subject rules
PrerequisitesSTA2MD OR STM2PM
Co-requisitesN/A
Incompatible subjectsSTA4AS
Equivalent subjectsN/A
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Special conditionsN/A
Minimum credit point requirementN/A
Assumed knowledgeN/A
Learning resources
Time Series Analysis: Forecasting and Control
Resource TypeBook
Resource RequirementRecommended
AuthorBox, G.E.P. and Jenkins, G.M.
Year1976
Edition/VolumeN/A
PublisherREVISED ED., HOLDEN-DAY, 1976.
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Printed text available from University Bookshop
Resource TypeBook
Resource RequirementPrescribed
AuthorPaul Kabaila and Luke Prendergast
YearN/A
Edition/VolumeN/A
PublisherDepartment of Mathematics and Statistics
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Applied Multivariate Statistical Analysis
Resource TypeBook
Resource RequirementRecommended
AuthorJohnson, R.A. and Wichern, D.W.
Year2002
Edition/Volume5TH ED
PublisherPEARSON
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Mathematical Statistics and Data Analysis
Resource TypeBook
Resource RequirementRecommended
AuthorRice, J.A.
Year2007
Edition/Volume3RD EDN
PublisherDUXBURY
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/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
Intended Learning Outcomes
Subject options
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Melbourne (Bundoora), 2021, Semester 2, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorPaul Kabaila
Class requirements
LectureWeek: 30 - 42
Three 1.00 hour lecture per week on weekdays during the day from week 30 to week 42 and delivered via face-to-face.
PracticalWeek: 30 - 42
One 1.00 hour practical per week on weekdays during the day from week 30 to week 42 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
3-hour short answer Final Examination | N/A | N/A | No | 70 | SILO1, SILO2, SILO3, SILO4 |
5 Assignments (approx. 240 words each) | N/A | N/A | No | 30 | SILO1, SILO2, SILO3, SILO4 |