Semesters 1: Prof Andrew Forbes, Dept of Epidemiology & Preventive Medicine, Monash University
Semesters 2: Prof Rory Wolfe, Dept of Epidemiology & Preventive Medicine, Monash University
Mathematical Background for Biostatistics
8-12 hours total study time per week
Semester 1 & 2
Two written assignments, each worth 35% and submission of selected practical written exercises from 5 modules 30%.
Wackerly DD, Mendenhall W, Scheaffer RL. Mathematical Statistics with Applications, 7th edition, 2007, Wadsworth Publishing (ex Duxbury Press, USA) For details, including ISBN, see the BCA Textbook and Software Guide
Stata or R statistical software, WolframAlpha
This unit begins with the study of probability, random variables, discrete and continuous distributions, and the use of calculus to obtain expressions for parameters of these distributions such as the mean and variance. Joint distributions for multiple random variables are introduced together with the important concepts of independence, correlation and covariance, marginal and conditional distributions. Techniques for determining distributions of transformations of random variables are discussed. The concept of the sampling distribution and standard error of an estimator of a parameter is presented, together with key properties of estimators. Large sample results concerning the properties of estimators are presented with emphasis on the central role of the normal distribution in these results. General approaches to obtaining estimators of parameters are introduced. Numerical simulation and graphing with Stata are used throughout to demonstrate concepts.
Course notes, assignment material and interaction facilities available online