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EPM5026 · Mathematical foundations for biostatistics

Official Handbook

2026 Handbook6 credit pointsLevel 5Department of Epidemiology and Preventive Medicine

Last checked: 23 Aug 2026 UTC

Overview

This unit covers the foundational mathematical methods and probability distribution concepts necessary for an in depth understanding of biostatistical methods. The unit commences with an introduction to mathematical expressions, followed by the fundamental calculus techniques of differentiation and integration, and essential elements of matrix algebra. The concepts and rules of probability are then introduced, followed by the application of the calculus methods covered earlier in the unit to calculate fundamental quantities of probability distributions, such as mean and variance. Random variables, their meaning and use in biostatistical applications is presented, together with the role of numerical simulation as a tool to demonstrate the properties of random variables.

Offerings

CampusTeaching periodMode
Alfred HospitalFirst semesterTeaching is all online (ONLINE)
Alfred HospitalSecond semesterTeaching is all online (ONLINE)

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

#AssessmentTypeWeightHurdle
1Written mathematical assignment (Equivalent to 2,100 words)Written35%
2 Written analytical probability exercises (Equivalent to 2,100 words)Exercise35%
3Two written short analytical exercises (15% each) (Equivalent to 1,800 words)Exercise30%

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

  1. Manipulate general mathematical expressions and inequalities.
  2. Manipulate general mathematical expressions and inequalities.
  3. Manipulate and evaluate matrix expressions and calculate inverses of matrices.
  4. Explain and apply the laws of probability to statistical problems.
  5. Recognise common probability distributions and their properties.
  6. Apply calculus-based tools to derive key features of a probability distribution and properties of random variables, such as mean and variance.
  7. Effectively program numerical simulation of random variables to illustrate and explain statistical concepts.

Workload

Off-Campus - Twelve hours per week, consisting of (on average) 4 hours per week for reading core material, 4 hours per week completing exercises (manual, computer-based, or on-line), 2 hours per week for on-line communication via online moderated discussions, and 2 hours per week for assignment preparation. No residential component is required.

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