Mathematical Foundations for Biostatistics (MFB)

This unit aims to develop and apply calculus and other mathematically-based techniques to the study of probability and statistical distributions. These two units, together with the subsequent Principles of Statistical Inference (PSI) unit, will provide the core prerequisite mathematical statistics background required for the study of later units in the Graduate Diploma or Masters degree

Andrew Forbes
Prof Andrew Forbes Monash University, Department of Epidemiology and Preventive Medicine Semester 1
Rhys Bowden profile photo
Dr Rhys Bowden Monash University, Department of Epidemiology and Preventive Medicine Semester 1
Dr Shenal Dedduwakumara University of Adelaide, School of Public Health Semester 2
General outline



Time commitment

8 -12 hours total study time per week, depending on the amount of revision required

Semester availability

Semester 1 & 2


Two written assignments, each worth 35% and submission of selected practical written exercises from modules, worth 30%.

Prescribed Texts

Wackerly DD, Mendenhall W, Scheaffer RL. Mathematical Statistics with Applications, 7th edition, 2007, Wadsworth Publishing (ex Duxbury Press, USA)

Recommended Texts

Healy, MJR. Matrices for Statistics, 2nd edition. Oxford University Press, 2000

Special Computer Requirements

Stata or R statistical software, and Wolfram Alpha (online free resource)


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.


Course notes, online mini-lecture videos, online tutorials, discussion board.

The BCA acknowledges we live and work on the ancestral lands of Aboriginal and Torres Strait Islander peoples, who have for thousands of generations exchanged knowledge for the benefit of all. We pay our respects to those who have cared and continue to care for Country.