Inference for Spatio-Temporal Processes (MAST90122)

Graduate courseworkPoints: 12.5On Campus (Parkville)

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Overview

Availability
Semester 1
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Modern data collection technologies are creating unprecedented challenges in statistics and data science related to the analysis and interpretation of massive data sets where observations exhibit patterns through time and space. This subject introduces probability models and advanced statistical inference methods for the analysis of temporal and spatio-temporal data. The subject balances rigorous theoretical development of the methods and their properties with real-data applications. Topics include inference methods for univariate and multivariate time series models, spatial models, lattice models, and inference methods for spatio-temporal processes. The subject will also address aspects related to computational and statistical trade-offs, and the use of statistical software.

Intended learning outcomes

On completion of this subject students should:

  • Have an understanding of selected advanced topics in spatio-temporal statistics;
  • Have developed mathematical and computational skills needed for further research or applied work in statistics and data science;
  • Feel prepared for a research or industry career in statistics and data science; and
  • Have familiarity with several major texts spatio-temporal statistics.

Generic skills

In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. These include:

  • Problem-solving skills: the ability to engage with unfamiliar problems and identify relevant solution strategies;
  • Analytical skills: the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of analysis;
  • Collaborative skills: the ability to work in a team; and
  • Time-management skills: the ability to meet regular deadlines while balancing competing commitments.

Last updated: 4 March 2025

Eligibility and requirements

Prerequisites

One of

Code Name Teaching period Credit Points
MAST90082 Mathematical Statistics
Semester 1 (On Campus - Parkville)
 12.5
MAST90138 Multivariate Statistics for Data Science
Semester 2 (On Campus - Parkville)
 12.5

Corequisites

None

Non-allowed subjects

None

Inherent requirements (core participation requirements)

The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.

Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home

Last updated: 4 March 2025

Assessment

DescriptionTimingPercentage

Up to 60 pages of written assignments (three assignments worth 10% each) due in weeks 4, 8 and 12

  • 60 pages
From Week 4 to Week 1230%

Written examination

  • 3 hours
During the examination period70%

Last updated: 4 March 2025

Dates & times

  • Semester 1
    Principal coordinatorTingjin Chu
    Mode of deliveryOn Campus (Parkville)
    Contact hours36 hours comprising 2 x one hour lectures per week, 1 x one hour practice class per week.
    Total time commitment170 hours
    Teaching period 3 March 2025 to 1 June 2025
    Last self-enrol date14 March 2025
    Census date31 March 2025
    Last date to withdraw without fail 9 May 2025
    Assessment period ends27 June 2025

    Semester 1 contact information

    tingjin.chu@unimelb.edu.au

What do these dates mean

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  • Your tuition fees, academic transcript and statements.
  • And for Commonwealth Supported students, your:
       -  Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
     

    Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.

Last updated: 4 March 2025

Further information

  • Texts

    Prescribed texts

    There are no specifically prescribed or recommended texts for this subject.

  • Available through the Community Access Program

    About the Community Access Program (CAP)

    This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.

    Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants

    Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.

  • Available to Study Abroad and/or Study Exchange Students

    This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.

Last updated: 4 March 2025