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A successful data analyst, scientist or data manager must have the ability to collect, analyse and interpret data in robust and meaningful ways. Central to this skillset is the ability to create hypotheses and test these using rigorous processes. This unit introduces the key concepts of study design and analysis. You will learn to formulate experimental aims, collect, interpret and analyse data to test specific hypotheses, and draw evidence-based conclusions. You will develop the skills and understanding of concepts such as controls, replicates, sample size, dependent and independent variables, and good research practice such as blinding and randomisation. You will emerge with a comprehensive understanding of how to optimise a product or web design and determining the effectiveness of new programs or solutions to understand if the observed changes in your data are systematic or if they may have happened by chance.
Study level | Postgraduate |
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Academic unit | Mathematics and Statistics Academic Operations |
Credit points | 6 |
Prerequisites:
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None |
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Corequisites:
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None |
Prohibitions:
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None |
Assumed knowledge:
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Fundamentals of statistics and coding in R, e.g. ODAT5011: Data Analytics Foundations |
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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PG Online Session 1A 2025
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Online | Online Program |
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