STAT4022: Linear and Mixed Models
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Unit of study_

STAT4022: Linear and Mixed Models

2025 unit information

Classical linear models are widely used in science, business, economics and technology. This unit will introduce the fundamental concepts of analysis of data from both observational studies and experimental designs using linear methods, together with concepts of collection of data and design of experiments. You will first consider linear models and regression methods with diagnostics for checking appropriateness of models, looking briefly at robust regression methods. Then you will consider the design and analysis of experiments considering notions of replication, randomisation and ideas of factorial designs. Throughout the course you will use the R statistical package to give analyses and graphical displays. This unit includes material in STAT3022 Applied Linear Models, but has an additional component on the mathematical techniques underlying applied linear models together with proofs of distribution theory based on vector space methods.

Unit details and rules

Managing faculty or University school:

Science

Study level Undergraduate
Academic unit Mathematics and Statistics Academic Operations
Credit points 6
Prerequisites:
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An average mark of 65 or above in 12 credit points from (STAT2X11 or DATA2X02 or STAT3X23 or STAT3X21 or STAT3925 or STAT3888 or DATA3888)
Corequisites:
? 
None
Prohibitions:
? 
STAT3012 or STAT3912 or STAT3022 or STAT3922 or STAT3004 or STAT3904
Assumed knowledge:
? 
Material in DATA2X02 or equivalent and MATH1002 or MATH1X61 or equivalent; that is, a knowledge of applied statistics and an introductory knowledge to linear algebra, including eigenvalues and eigenvectors

At the completion of this unit, you should be able to:

  • LO1. Apply and formulate appropriate linear models to analyse data from diverse settings, including cross-sectional studies, experiments, panel studies
  • LO2. Apply, analyse, and implement least square estimators for parameters in linear models
  • LO3. Calculate and interpret interval estimators, including confidence intervals and prediction intervals, for appropriate quantities in linear models
  • LO4. Conduct appropriate hypothesis testings for parameters in linear models
  • LO5. Conduct appropriate diagnostics to check model assumptions and detect unusual observations
  • LO6. Apply, implement, and interpret the results from likelihood-based methods to fit linear mixed effects models
  • LO7. Derive and re-create proofs of theoretical aspects of linear models.

Unit availability

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 ? 
Semester 1 2025
Normal day Camperdown / Darlington, Sydney
Session MoA ?  Location Outline ? 
Semester 1 2020
Normal day Camperdown / Darlington, Sydney
Outline unavailable
Semester 1 2021
Normal day Camperdown / Darlington, Sydney
Semester 1 2021
Normal day Remote
Semester 1 2022
Normal day Camperdown / Darlington, Sydney
Semester 1 2022
Normal day Remote
Semester 1 2023
Normal day Camperdown / Darlington, Sydney
Semester 1 2024
Normal day Camperdown / Darlington, Sydney

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Modes of attendance (MoA)

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