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Master of Biostatistics

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  • Objectives
    On completion of the Master of Biostatistics, graduates will: * have developed a sound understanding of epidemiological study design and the theory and application of the major areas of biostatistics relevant to professional practice * have acquired skills in complex statistical analyses to handle a variety of practical problems using modern statistical techniques and software * have acquired skills in data collection and data management, including database design, quality control procedures and the ethical handling of data * have developed skills to identify the relevant statistical issues in practical problems in medical/health settings and to propose and implement an appropriate statistical design and/or analysis methodology * have developed skills and had experience in communication of biostatistical issues with clinical/health personnel and the presentation of statistical results in a format suitable for publication in health-related journals or professional reports * have acquired the technical skills to be able to read methodological papers in the biostatistical literature and apply the methods described therein to practical problems * have developed the practical and technical skills to commence professional careers as independent biostatisticians and/or to progress to further postgraduate research studies * be able to demonstrate an understanding of professional codes of conduct and ethical standards such as those of the Statistical Society of Australia * have developed problem solving abilities in biostatistics, characterised by flexibility of approach
  • Academic Title
    Master of Biostatistics
  • Course description
    Option 1: 10 coursework subjects and a two unit Workplace project portfolio (150 points)
    Option 2: 11 coursework subjects and a one unit Workplace project portfolio (150 points)

    Students may be waived the requirement to complete either Epidemiology (most likely students coming from a background in health research), or one or more of the units, Mathematical Background for Biostatistics, Probability and Distribution Theory and Principles of Statistical Inference (most likely students coming from a background in mathematics and/or statistics), if they have equivalent prior studies. This should leave room for the student to complete one or two electives in addition to the compulsory Workplace Project Portfolio unit (WPP). Students may receive credit for subjects previously completed while enrolled at the Postgraduate Certificate and Postgraduate Diploma levels.


    Students must complete the following core subjects:

    Subject     Semester     Credit Points
    505-942  Survival Analysis
    Topics include: Kaplan-Meier life tables; logrank test to compare two or more groups; Cox's proportional hazards regression model; checking the proportional hazards assumption; time-dependent covariates; sample size calculations for survival stu...     Semester 1     12.50

    505-108  Data Management & Statistical Computing
    Topics include data management concepts, introduction to Stata and SAS, data management using Stata and SAS. Data management principles and concepts are developed using relational database software (Microsoft Access). Data manipulation, descriptive a...     Semester 1, Semester 2     12.50

    505-106  Epidemiology
    Topics include: historical developments in epidemiology; sources of data on mortality and morbidity; disease rates and standardisation; prevalence and incidence; life expectancy; linking exposure and disease (e.g. relative risk, attributable risk); m...     Semester 1, Semester 2     12.50

    505-105  Mathematics B'Ground for Biostatistics
    Basic algebra and analysis; exponential functions; calculus; series, limits, approximations and expansions; matrices and numerical methods.     Semester 1, Semester 2     12.50

    505-107  Principles of Statistical Inference
    Review of the key concepts of estimation, and construction of Normal-theory confidence intervals; frequentist theory of estimation including hypothesis tests; methods of inference based on likelihood theory, including use of Fisher and observed infor...     Semester 1, Semester 2     12.50

    505-941  Categorical Data & GLMs
    Introduction to and revision of conventional methods for contingency tables especially in epidemiology: odds ratios and relative risks, chi-squared tests for independence, Mantel-Haenszel methods for stratified tables, and methods for paired data. T...     Semester 2     12.50

    505-939  Design of Randomised Controlled Trials
    Topics include: principles and methods of randomisation in controlled trials; treatment allocation, blocking, stratification and allocation concealment; parallel, factorial and crossover designs including n-of-1 studies; practical issues in sample si...     Semester 2     12.50

    505-940  Linear Models
    The method of least squares; regression models and related statistical inference; flexible nonparametric regression; analysis of covariance to adjust for confounding; multiple regression with matrix algebra; model construction and interpretation (use...     Semester 2     12.50

    505-975  Probability and Distribution Theory
    This subject 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 mul...     Semester 1, Semester 2     12.50


    Students must also complete one of the following workplace project portfolio subjects (depending on the structure of their program):

    Subject     Semester     Credit Points
    505-976  Workplace Project Portfolio - S (WPP)
    The student will provide evidence of having met this goal by presenting a portfolio or minor dissertation made up of a preface and project reports. An outline of the options for the structure of this subject, including supervision and assessment requ...     Semester 1, Semester 2     12.50

    505-945  Workplace Project Portfolio - L (WPP)
    The student will provide evidence of having met this goal by presenting a portfolio or minor dissertation made up of a preface and project reports. An outline of the options for the structure of this subject, including supervision and assessment requ...     Semester 1, Semester 2     25

    505-978  Workplace Project Portfolio - D (WPP)
    The student will provide evidence of having met this goal by presenting a portfolio or minor dissertation made up of a preface and project reports. An outline of the options for the structure of this subject, including supervision and assessment requ...     Semester 1, Semester 2     25


    Subject     Semester     Credit Points

    505-938  Clinical Biostatistics
    Clinical agreement (kappa statistics, Bland-Altman agreement method, intraclass correlation); diagnostic tests (sensitivity, specificity, predictive values, ROC curves, likelihood ratio); statistical process control (special and common causes of var...     Semester 1     12.50

    505-937  Health Indicators and Health Surveys
    Topics include: routinely collected health-related data; quantitative methods in demography, including standardisation and life tables; health differentials; design and analysis of population health surveys, including the role of stratification, clus...     Semester 1     12.50

    505-943  Longitudinal and Correlated Data
    Topics covered: Paired data; the effect of non-independence on comparisons within and between clusters of observations; methods for continuous outcomes: normal mixed effects (hierarchical or multilevel) models and generalised estimating equations (GE...     Semester 1     12.50

    505-964  Advanced Clinical Trials
    Methods in RCTs for determining: stopping rules for interim analysis (O’Brien-Fleming, Peto), spending functions, stochastic curtailment; statistical principles encountered in relation to aspects of regulatory guidelines (ICH, FDA, EMEA)...     Semester 2     12.50

    505-944  Bioinformatics
    Bioinformatics addresses problems related to the storage, retrieval and analysis of information about biological structure. This unit will provide a broad-ranging study of this application of quantitative methods in biology. Content will include: bio...     Semester 2     12.50

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