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

PrerequisitesSTM2PM OR STA2MD

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

Readings

Applied Multivariate Statistical Analysis

Resource TypeRecommended

Resource RequirementN/A

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 TypeRecommended

Resource RequirementN/A

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

Printed text available from University Bookshop

Resource TypePrescribed

Resource RequirementN/A

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

Time Series Analysis: Forecasting and Control

Resource TypeRecommended

Resource RequirementN/A

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

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

01. Present clear, well structured proofs of important fundamental results in sample surveys, multivariate analysis and Box-Jenkins univariate time series analysis. This includes clear and concise use of statistical and mathematical vocabulary and notation.
02. Describe and use key sample survey, multivariate analysis and Box-Jenkins univariate time series analysis tools including a justification of appropriate usage based on known model/data conditions
03. Understand some methods of model checking in the context of multivariate analysis.
04. Present clear written communications of statistical results in a manner which can be understood by a scientist who fully understands the variables in the associated data set, but who has only a basic understanding of statistics.

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2021, Semester 2, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorPaul Kabaila

Class requirements

Lecture Week: 31 - 43
Three 1.00 h lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Practical Week: 31 - 43
One 1.00 h practical per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*
3-hour short answer Final ExaminationN/AN/AN/ANo70 SILO1, SILO2, SILO3, SILO4
5 Assignments (approx. 240 words each)N/AN/AN/ANo30 SILO1, SILO2, SILO3, SILO4