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Predictive Business Analytics (BUSA90541)

Graduate courseworkPoints: 12.5On Campus (Parkville)

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Overview

Availability
May
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Predicting key business and economic variables is increasingly important, as it drives both objective decision-making and improved profitability. This component aims to cover the main methods used to predict business and economic variables, based on historical data. These include traditional regression, time series, multivariate and econometric models, as well as emerging methods such as ensemble forecasts. Both point and density prediction will be considered, along with metrics for the quality of both. Throughout, the focus will be on introducing methods in the context of substantive business and economic problems, using a wide range of prediction methods. The importance of benchmarking different methodologies, and the use of prediction in decision-making frameworks, will also be stressed.

Intended learning outcomes

On completion of this subject, students should be able to:

  • Understand a wide range of models and methodologies relevant to predicting business outcomes.
  • Apply appropriate modelling and forecasting techniques to business and economic contexts, and to critique and compare competing methodologies.
  • Translate forecasting outputs to information and provide recommendations to address the relevant business problems.

Last updated: 31 January 2024

Eligibility and requirements

Prerequisites

Pre-requisite

Code Name Teaching period Credit Points
BUSA90536 Statistical Learning for Business
March (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: 31 January 2024

Assessment

DescriptionTimingPercentage

Individual assignment

  • 1000 words
Week 320%

Syndicate assignment

  • 1500 words (equivalent)
Week 630%

Final examination

  • 2 hours
Hurdle requirement: Students are required to pass the final examination to pass the subject		Week 950%

Last updated: 31 January 2024

Dates & times

  • May
    Mode of deliveryOn Campus (Parkville)
    Contact hours
    Total time commitment170 hours
    Teaching period27 May 2024 to 19 July 2024
    Last self-enrol date 6 June 2024
    Census date14 June 2024
    Last date to withdraw without fail 5 July 2024
    Assessment period ends26 July 2024

What do these dates mean

Visit this webpage to find out about these key dates, including how they impact on:

  • 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: 31 January 2024

Further information

  • Texts

    Prescribed texts

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

Last updated: 31 January 2024