Graduate Diploma in Biostatistics (GD-BIOSTAT)
Graduate DiplomaYear: 2025 Delivered: On Campus (Parkville)
About this course
Coordinator
Emily Karahalios
Contact
emily.karahalios@unimelb.edu.au
Melbourne School of Population and Global Health
OR
Currently enrolled students:
Future Students:
- Further Information: https://study.unimelb.edu.au/
Overview
Award title | Graduate Diploma in Biostatistics |
---|---|
Year & campus | 2025 — Parkville |
CRICOS code | 088479M |
Fees information | Subject EFTSL, level, discipline and census date |
Study level & type | Graduate Coursework |
AQF level | 8 |
Credit points | 100 credit points |
Duration | 12 months full-time or 24 months part-time |
The Graduate Diploma in Biostatistics provides advanced biostatistical training with a solid foundation in mathematics and probability for a diverse range of students. Graduates acquire specialised knowledge and skills in the statistical methods used in health and medical investigations, with the necessary mathematical foundation to integrate sophisticated statistical understanding and specialised skills into their training. On completion of the Graduate Diploma, graduates will have attained the required skills for employment as a biostatistician.
Please note: mid-year intake to this course is not available for international students.
Entry requirements
1. In order to be considered for entry, applicants must have completed:
- A Bachelor degree in a relevant discipline, such as statistics, mathematics, biomedicine, psychology, science, pharmacy, health sciences, economics, from an approved university, with an average mark over the degree of at least 70% or equivalent; and
- Successful completion (average mark of 65%) at tertiary level of at least one mathematics subject, including elements of multivariable calculus and linear algebra.
Applicants may be required to attend a test to elucidate any of the matters listed above.
2. In ranking applications, the Selection Committee will consider:
- Prior academic performance; and
- Where relevant, performance in an interview or test, and/or referee reports or employer references.
3. The Selection Committee may seek further information to clarify any aspect of an application in accordance with the Academic Board rules on the use of selection instruments.
4. Applicants are required to satisfy the university’s English language requirements for postgraduate courses. For those applicants seeking to meet these requirements by one of the standard tests approved by the Academic Board, performance Band 6.5 is required.
Inherent requirements (core participation requirements)
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this course are articulated in the Course Description, Course Objectives and Generic Skills of this entry.
The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website.
Professional accreditation
The Graduate Diploma in Biostatistics course is accredited by the Statistical Society of Australia, which means that graduates automatically qualify for registration with the professional qualification of Graduate Statistician.
Intended learning outcomes
On completion of the Graduate Diploma in Biostatistics, graduates will be able to:
Knowledge
- Explain key concepts of quantitative research methods including the role of statistical methods in drawing inferences from data
- Demonstrate a sound understanding of the theory underlying the main areas of biostatistics relevant to professional practice and research
- Explain key epidemiological concepts including measures of disease frequency and causal effect, and the major sources of bias in epidemiological studies.
Skills
- develop research questions (descriptive, causal, predictive) and corresponding appropriate statistical designs and/or analysis methods in medical/health settings
- display skills in a range of complex statistical analyses using modern statistical software and programming skills
- demonstrate skills in data collection and data management, including database design, quality control procedures and the ethical handling of data
- employ sound communication skills relating to biostatistical issues with clinical/health professionals including appropriate presentation of statistical material
- display the technical skills to be able to read methodological papers in the biostatistical literature and apply the methods described therein to practical problems
Application of knowledge and skills
- display problem-solving abilities in biostatistics, characterised by flexibility of approach
Generic skills
- Communicate effectively to a range of audiences
- Think critically to answer research questions in the medical/health field
- Effectively organize, time manage and plan
- Demonstrate the technical skills for professional practice.
Graduate attributes
The Melbourne Experience enables our graduates to become:
Academically excellent:
- Have a strong sense of intellectual integrity and the ethics of scholarship
- Have in-depth knowledge of their specialist discipline(s)
- Reach a high level of achievement in writing, generic research activities, problem-solving and communication
- Be critical and creative thinkers, with an aptitude for continued self-directed learning
- Be adept at learning in a range of ways, including through information and communication technologies.
Knowledgeable across disciplines:
- Examine critically, synthesise and evaluate knowledge across a broad range of disciplines
- Expand their analytical and cognitive skills through learning experiences in diverse subjects
- Have the capacity to participate fully in collaborative learning and to confront unfamiliar problems
- Have a set of flexible and transferable skills for different types of employment.
Leaders in communities:
- Initiate and implement constructive change in their communities, including professions and workplaces
- Have excellent interpersonal and decision-making skills, including an awareness of personal strengths and limitations
- Mentor future generations of learners
- Engage in meaningful public discourse, with a profound awareness of community needs.
Attuned to cultural diversity:
- Value different cultures
- Be well-informed citizens able to contribute to their communities wherever they choose to live and work
- Have an understanding of the social and cultural diversity in our community
- Respect indigenous knowledge, cultures and values.
Active global citizens:
- Accept social and civic responsibilities
- Be advocates for improving the sustainability of the environment
- Have a broad global understanding, with a high regard for human rights, equity and ethics.
Course structure
FIVE core subjects and THREE electives (100 points)
CORE SUBJECTS
Students must complete the following FIVE CORE subjects:
Code | Name | Study period | Credit Points |
---|---|---|---|
MAST90100 | Probability & Inference in Biostatistics | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
POPH90014 | Epidemiology 1 |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
MAST90101 | Introduction to Statistical Computing | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
MAST90102 | Foundations of Regression | July (Dual-Delivery - Parkville) |
12.5 |
Code | Name | Study period | Credit Points |
---|---|---|---|
MAST90099 | Advanced Regression | September (Dual-Delivery - Parkville) |
12.5 |
ELECTIVE SUBJECTS
Students must choose THREE subjects from the following list of electives:
Code | Name | Study period | Credit Points |
---|---|---|---|
POPH90118 | Clinical Biostatistics | Semester 1 (Online) |
12.5 |
POPH90117 | Health Indicators and Health Surveys | Semester 1 (Online) |
12.5 |
POPH90123 | Longitudinal and Correlated Data |
Semester 1 (Online)
Semester 2 (Online)
|
12.5 |
Code | Name | Study period | Credit Points |
---|---|---|---|
ISYS90069 | Digital Transformation of Health |
Semester 1 (On Campus - Parkville)
July (Online)
|
12.5 |
POPH90124 | Statistical Genomics | Not available in 2025 | 12.5 |
MAST90140 | Causal Inference | Semester 1 (Online) |
12.5 |
Code | Name | Study period | Credit Points |
---|---|---|---|
MAST90083 | Computational Statistics & Data Science | Semester 2 (On Campus - Parkville) |
12.5 |
POPH90119 | Design of Randomised Controlled Trials | Semester 2 (Online) |
12.5 |
MAST90027 | Practice of Statistics & Data Science | Not available in 2025 | 12.5 |
POPH90242 | Epidemiology 2 | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
INFO90002 | Database Systems & Information Modelling |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP90041 | Programming and Software Development |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
POPH90139 | Bayesian Statistical Methods | Semester 2 (Online) |
12.5 |
POPH90094 | Health Economics 1 | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
SCIE90013 | Communication for Research Scientists |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
MAST90141 | Machine Learning for Biostatistics | Semester 2 (Online) |
12.5 |
POPH90112 | Infectious Disease Epidemiology | April (Dual-Delivery - Parkville) |
12.5 |
Last updated: 27 February 2025