Mathematical Background for Statistics


Covers the necessary mathematical background to understand the key techniques in biostatistics.

This course is offered in conjunction with the Biostatistics Collaboration of Australia (BCA).


Distance Education - Callaghan

  • Semester 1 - 2016
  • Semester 2 - 2016
  • Semester 1 - 2017
  • Semester 2 - 2017

Learning Outcomes

On successful completion of the course students will be able to:

1. Manipulate general mathematical expressions and inequalities;

2. Understand the notion of a limit and calculate simple limits;

3. Understand the notion of the derivative and its applications, and calculate simple derivatives;

4. Understand the notion of the integral and its applications, and calculate simple integrals;

5. Manipulate and evaluate simple matrix expressions;

6. Understand matrix concepts such as determinant, inverse, rank, orthogonal matrix, eigenvalues and eigenvectors;

7. Appreciate the nature and importance of mathematical arguments.


This course covers core topics in algebra and analysis, including polynomial and simultaneous equations, graphs, the concept of limits, continuity and series approximations, including Taylor series expansions. Calculus will be introduced describing the techniques of integration and differentiation of vector expressions. This will be integrated into a study of probability, where the concepts of probability laws, random variables, expectation and distributions will be introduced. Essential topics in matrix algebra relevant to biostatistical methods will be presented. Finally, essential numerical methods, including the Newton-Raphson method for solution of simultaneous equations and concepts of numerical integration will be introduced.


This course is only available to students enrolled in the Graduate Diploma in Medical Statistics or Master of Medical Statistics programs.

Assessment Items

Written Assignment: Essays / Written Assignments

Contact Hours

Distance Education - Callaghan

Self-Directed Learning

Self-Directed 6 hour(s) per Week for Full Term

Suggest 8-10 hours per week time allocation (guide only)