Sydney Professional Certificate

Biostatistics in Health

Graduates of this Professional Certificate will have specialised knowledge in Biostatistics in Health.

Graduates will have cognitive skills to:

  • Review, analyse, consolidate and synthesise statistical methods used in health research
  • Apply statistical methods to issues in health research
  • Apply biostatistical knowledge and skills in health research to best communicate research findings in their professional practice.

 

Unit of study Credit points A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition Session

Biostatistics in Health

Sydney Professional Certificate in Biostatistics

Students must complete:
(a) 12 credit points of 5000-level units of study
5000-level units of study
PUBH5018
Introductory Biostatistics
6      Semester 1
PUBH5217
Biostatistics: Statistical Modelling
6    P PUBH5018
N (PUBH5211 or PUBH5212 or PUBH5213)


The statistical software package used in this unit is web-based. There is no cost/fee to use this software.
Semester 2

Biostatistics in Health

Sydney Professional Certificate in Biostatistics

Students must complete:
(a) 12 credit points of 5000-level units of study
5000-level units of study
PUBH5018 Introductory Biostatistics

Credit points: 6 Teacher/Coordinator: Dr Timothy Schlub, Dr Erin Cvejic Session: Semester 1 Classes: 2 x 2hr lectures, 10 x 1hr lectures, 11 x 2hr tutorials, 2 x 1hr and 8 x 0.5hr statistical computing self directed learning tasks over 12 weeks - lectures and tutorials may be completed online Assessment: Weekly quizzes (10%), 1x4 page assignment (20%), 1x1hr online test (20%) and 1x1.5hr open-book exam (50%). For distance students it may be possible to complete the exam externally with the approval of the course coordinator. Mode of delivery: Normal (lecture/lab/tutorial) day, Normal (lecture/lab/tutorial) evening, Online
This unit introduces students to statistical methods relevant in medicine and health. Students will learn how to appropriately summarise and visualise data, carry out a statistical analysis, interpret p-values and confidence intervals, and present statistical findings in a scientific publication. Students will also learn how to determine the appropriate sample size when planning a research study. Students will learn how to conduct analyses using calculators and statistical software.
Specific analysis methods of this unit include: hypothesis tests for one-sample, two paired samples and two independent samples for continuous and binary data; distribution-free methods for two paired samples, two independent samples; correlation and simple linear regression; power and sample size estimation for simple studies; and introduction to multivariable regression models;.
Students who wish to continue with their statistical learning after this unit are encouraged to take PUBH5217 Biostatistics: Statistical Modelling.
Textbooks
Course notes will be made available.
PUBH5217 Biostatistics: Statistical Modelling

Credit points: 6 Teacher/Coordinator: Associate Professor Patrick Kelly, Associate Professor Kevin McGeechan Session: Semester 2 Classes: 1.5hr lecture and 2hr computer lab/tutorial per week for 13 weeks Prerequisites: PUBH5018 Prohibitions: (PUBH5211 or PUBH5212 or PUBH5213) Assessment: 1x 4pg data analysis assignment (equivalent to 1200wds) (25%) and 10x online quizzes (15%) and 1x 10pg data analysis assignment (equivalent to 3000wds) (60%) Mode of delivery: Normal (lecture/lab/tutorial) day, Online
Note: The statistical software package used in this unit is web-based. There is no cost/fee to use this software.
In this unit, you will learn how to analyse health data using statistical models. In particular, how to fit and interpret the results of different statistical models which are commonly used in medicine and health research: linear models, logistic models, and survival models. This unit is ideal for those who wish to further develop their research skills and/or improve their literacy in reading and critiquing journal articles in medicine and health.
The focus of the unit is very applied and not mathematical. Students gain hands on experience in fitting statistical models in real data. You will learn how to clean data, build an appropriate model, and interpret results. This unit serves as a prerequisite for PUBH5218 Advanced Statistical Modelling.
Textbooks
Course notes are provided.