SPATIAL ANALYSIS

STA4SA

2021

Credit points: 15

Subject outline

The subject surveys the theory of random fields, spatial processes, spatial statistics models, and their applications to a wide range of areas, including image analysis and GIS (geographic information system). The subject will cover the methodology and modern developments for spatial-temporal modelling, estimation and prediction, and spectral analysis of spatial processes. All the methods presented will be introduced in the context of specific datasets with GRASS and R software.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorAndriy Olenko

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 4 - UG/Hons/1st Yr PG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

Prerequisites STA3AS or STA4AS and (STA3SI or STM3SI) or (STA4SI or STM4SI) or enrolment into SMDS

Co-requisitesN/A

Incompatible subjectsN/A

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsA sufficient background in probability and statistics is required to undertake this subject.

Minimum credit point requirementN/A

Assumed knowledgeN/A

Readings

Analysing spatial point patterns in R.

Resource TypeRecommended

Resource RequirementN/A

AuthorBaddeley, A.

Year2008

Edition/VolumeN/A

PublisherWORKSHOP NOTES, VERSION 3.

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Applied spatial analysis with R

Resource TypeRecommended

Resource RequirementN/A

AuthorBivand, R.S., Pebesma, E. J., Gomez-Rubio, V.

Year2008

Edition/VolumeN/A

PublisherSPRINGER.

ISBNN/A

Chapter/article titleN/A

Chapter/issueN/A

URLN/A

Other descriptionN/A

Source locationN/A

Statistics for spatial data

Resource TypeRecommended

Resource RequirementN/A

AuthorCressie, N.A.C

Year1993

Edition/VolumeN/A

PublisherWILEY

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. Formulate purposeful questions to explore new statistical ideas and subsequently design valid statistical experiments.
02. Present clear, well structured proofs of important theoretical statistical model results.
03. Creatively find solutions to real world problems consistent with those commonly faced by practicing statisticians.
04. Professionally defend or question the validity of existing statistical analyses and associated evidence-based conclusions that are derived via application of sound spatial statistical methodology.

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2021, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Subject Instance Co-ordinatorAndriy Olenko

Class requirements

Lecture/PracticalWeek: 10 - 22
One 2.00 h lecture/practical per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Two contact hours per week.

Assessments

Assessment elementCommentsCategoryContributionHurdle% ILO*
Four assignments (approx. 400 words each)N/AN/AN/ANo40 SILO1, SILO2, SILO3, SILO4
One 3-hour short answer Final Examination (approx. 3000 words)N/AN/AN/ANo60 SILO2, SILO3, SILO4