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Unit of study_
OLET5608: Linear Modelling
2023 unit information
Linear models form the bedrock of many real-world data analyses. They are versatile, interpretable and easily implemented. This unit provides an overview of two of the most common methods of statistical analysis of data: analysis of variance and regression. You will generate data visualisation and diagnostics plots to interpret and discover the limitations of linear models and identify when more complex approaches may be needed. You will learn to code your analyses and perform reproducible research using the open source statistical package R. A key component of this unit involves generating visualisations, estimating and selecting appropriate linear models using your data. By doing this unit you will learn how to generate, interpret, visualise, discover and critique linear models applied to your original research.
Unit details and rules
Managing faculty or University school:
Science
| Study level | Postgraduate |
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| Academic unit | Mathematics and Statistics Academic Operations |
| Credit points | 2 |
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Prerequisites:
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None |
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Corequisites:
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None |
| Prohibitions:
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DATA2002 or DATA2902 or ENVX2001 |
| Assumed knowledge:
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Exploratory data analysis, sampling, simple linear regression, t-tests and confidence intervals. Ability to perform data analytics with coding, basic linear algebra. E.g. DATA1001 and OLET5606 (Data wrangling) |
At the completion of this unit, you should be able to:
- LO1. formulate domain/context specific questions and identify appropriate statistical analysis
- LO2. generate, interpret and compare numerical and graphical summaries of different data types
- LO3. identify, justify, implement and evaluate appropriate parametric or non-parametric statistical tests for more than two samples
- LO4. generate, critique and interpret appropriate linear models to predict outcomes and describe relationships between multiple variables.
Unit availability
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