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This unit aims to provide a thorough and rigorous coverage of some of the statistical theory underpinning modern estimation methods in Business Statistics. Development of the material is rigorous, and comparisons are drawn between different approaches to estimation and inference. The theory is complemented with relevant business examples allowing students to gain a deep understanding of the models and the ability to tailor them to various business applications.
Code | BUSS4931 |
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Academic unit | Business Analytics |
Credit points | 6 |
Prerequisites:
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Students must meet the entry requirements for the Bachelor of Advanced Studies (Advanced Coursework), including completion of a pass undergraduate degree and a major in Business Analytics (including QBUS3600) |
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Corequisites:
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None |
Prohibitions:
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None |
Assumed knowledge:
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Students are assumed to be familiar with statistical modelling, Optimisation and Machine Learning |
At the completion of this unit, you should be able to:
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
Session | MoA ? | Location | Outline ? |
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Semester 1 2024
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Normal day | Camperdown/Darlington, Sydney |
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Session | MoA ? | Location | Outline ? |
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Semester 1 2021
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Normal day | Camperdown/Darlington, Sydney |
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Semester 1 2021
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Normal day | Remote |
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Semester 1 2022
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Normal day | Camperdown/Darlington, Sydney |
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Semester 1 2022
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Normal day | Remote |
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Semester 1 2023
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Normal day | Camperdown/Darlington, Sydney |
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Semester 1 2023
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Normal day | Remote |
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This refers to the Mode of attendance (MoA) for the unit as it appears when you’re selecting your units in Sydney Student. Find more information about modes of attendance on our website.