0 points, SCA Band 2, 0.000 EFTSL
Postgraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
Faculty
Medicine, Nursing and Health Sciences
Organisational Unit
Department of Epidemiology and Preventive Medicine
Coordinator(s)
Unit guides
Offered
- First semester 2017 (Day)
- First semester 2017 (Off-campus)
- Second semester 2017 (Off-campus)
Notes
HDR unit
Synopsis
This unit introduces students to biostatistics as applied to public health and management studies. Biostatistics is the science of describing, summarising, and analysing health-related data. It is essential to understand biostatistics in order to design, conduct, and interpret health-related research. The basic principles and methods used in biostatistics are covered in this unit, including the technical qualifications necessary for analysing and interpreting data on a descriptive and bivariate level.
Topics include classifying health data; summarising data using simple statistical methods and graphical presentation; sampling distributions; quantifying uncertainty in results from a sample; working with statistical distributions; comparing two or more groups/methods using confidence intervals and hypothesis tests (p - values); assessing the association between an outcome and an exposure using the chi-squared test; using risk comparisons (RR and OR); predicting an event or identifying risk factors for an event of interest where the event is measured on a continuous scale or a binary scale (yes/no).
Outcomes
Upon successful completion of this unit, students should be able to:
- Classify data into appropriate measurement types.
- Present data using relevant tables, graphical displays, and summary statistics, quantify uncertainty in study results.
- Formulate research hypotheses into a statistical context in public health studies.
- Estimate quantities of interest and evaluate hypothesis with appropriate statistical methods.
- Accurately interpret statistical methods and results reported in health publications.
- Analyse data using a specific software package.
Assessment
- Assignment 1 (maximum of 2,000 words) (15%)
- Assignment 2 (maximum of 2,500 words) (25%)
- Assignment 3 (maximum of 3,500 words) (40%)
- Online test (MCQ) (30 minutes) (20%)
Workload requirements
Sem 1 - DAY mode: 4 contact hours (2 hours lecture and 2 hours tutorial) + 2 hours online guided discussion + 6 hours independent study per week.
Sem 1 - DE mode: 24 contact hours over 3 days + 2 hours online tutorial exercises + 2 hours online guided discussion + 6 hours independent study per week.
Sem 2 - DE mode: 2 hours online lectures (recorded), 2 hours online tutorial exercises + 2 hours online guided discussion + 6 hours of independent study per week.
See also Unit timetable information
Chief examiner(s)
Off-campus attendance requirements
3 day on-campus block for off-campus students.
This unit applies to the following area(s) of study
Prerequisites
Students will be required to have basic computer literacy skills using Microsoft Windows, Word, Excel, and have access to a calculator equipped with elementary scientific functions (such as the Casio FX-100 calculator) and a statistical package for data analysis (support will be available for software package IBM SPSS).