Modern Applied Statistics (MAST30027)

Undergraduate level 3Points: 12.5On Campus (Parkville)

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Overview

Availability
Semester 2
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Modern applied statistics combines the power of modern computing and theoretical statistics. This subject considers the computational techniques required for the practical implementation of statistical theory, and includes Bayes and Monte-Carlo methods. The subject focuses on the application of these techniques to generalised linear models, which are commonly used in the analysis of categorical data.

Intended learning outcomes

At the completion of the subject, students should:

  • Explain the theory and applications of various mainstream applied statistical methods;
  • Apply appropriate statistical methods to develop effective models or inferential procedures and provide sound interpretations for real-world data analysis;
  • Perform statistical computation and data analysis using a computer package.

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 andexpress 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;
  • time management skills: the ability to meet regular deadlines while balancing competing commitments;
  • computer skills: the ability to use statistical computing packages.

Last updated: 4 March 2025

Eligibility and requirements

Prerequisites

Code Name Teaching period Credit Points
MAST30025 Linear Statistical Models
Semester 1 (On Campus - Parkville)
 12.5

Corequisites

None

Non-allowed subjects

Code Name Teaching period Credit Points
ACTL30004 Actuarial Statistics
Semester 2 (On Campus - Parkville)
 12.5
ACTL30001 Actuarial Modelling I
Semester 1 (On Campus - Parkville)
 12.5

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

Four written (derivation and analysis based) assignments; Major components in assignments are data analysis and there will be some mathematical derivation as well. A total of up to 56 pages, requiring approximately 50 hours work due in weeks 3, 6, 9 and 12

  • 56 pages
From Week 3 to Week 1240%

A written examination

  • 2.5 hours
Hurdle requirement: A minimum 40% mark on the examination for satisfactory completion.		During the examination period60%

Last updated: 4 March 2025

Dates & times

  • Semester 2
    CoordinatorHeejung Shim
    Mode of deliveryOn Campus (Parkville)
    Contact hours3 x one hour lectures per week, 1 x one hour computer laboratory class per week
    Total time commitment170 hours
    Teaching period28 July 2025 to 26 October 2025
    Last self-enrol date 8 August 2025
    Census date 1 September 2025
    Last date to withdraw without fail26 September 2025
    Assessment period ends21 November 2025

    Semester 2 contact information

    heejung.shim@unimelb.edu.au

Time commitment details

Estimated total time commitment of 170 hours

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

Last updated: 4 March 2025