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Unit of study_
STAT2011: Probability and Estimation Theory
2026 unit information
This unit offers a foundational introduction to probability theory and statistical inference, focusing on key concepts such as random variables and widely used probability distributions—including the Binomial, Hypergeometric, Poisson, Normal, Geometric, and Gamma distributions. Students will engage with univariate data analysis techniques and gain practical skills in modelling variability using real-world data. Core estimation methods, including the method of moments, maximum likelihood estimation, and associated inference procedures are introduced in a rigorous yet accessible manner. Weekly computer laboratory sessions provide hands-on experience with statistical software for simulation, distribution fitting, and computational methods such as the bootstrap. By the end of the unit, students will have developed essential statistical modelling competencies, equipping them for further study in advanced statistical analysis and data science.
Unit details and rules
Managing faculty or University school:
Science
| Study level | Undergraduate |
|---|---|
| Academic unit | Mathematics and Statistics Academic Operations |
| Credit points | 6 |
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Prerequisites:
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(MATH1X61 or MATH1971 or MATH1X21 or MATH1931 or MATH1X01 or MATH1906 or MATH1011) and (DATA1X01 or MATH1X62 or MATH1972 or MATH10X5 or MATH1905 or STAT1021 or ECMT1010 or BUSS1020) |
|---|---|
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Corequisites:
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None |
| Prohibitions:
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STAT2911 |
| Assumed knowledge:
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None |
At the completion of this unit, you should be able to:
- LO1. construct appropriate statistical models involving random variables for a range of modelling scenarios. Compute (or approximate with a computer if necessary) numerical characteristics of random variables in these models such as probabilities, expectations and variances
- LO2. fit such models in outcome 1. to data (as appropriate) by estimating any unknown parameters
- LO3. compute appropriate (both theoretically and computationally derived) measures of uncertainty for any parameter estimates
- LO4. assess the goodness of fit (as appropriate) of a fitted model
- LO5. apply certain mathematical results (e.g. inequalities, limiting results) to problems relating to statistical estimation theory
- LO6. prove certain mathematical results (e.g. inequalities, limiting results) used in the course.
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 ? |
|---|---|---|---|
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Semester 1 2026
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Normal day | Camperdown/Darlington, Sydney |
Outline unavailable
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Modes of attendance (MoA)
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