TM5516 - Biostatistics for Public Health
|Student Contribution Band:
||College of Public Health, Medical & Vet Sciences
Available to all postgraduate students in health science programs.
Biostatistics for public health is an introductory level course that covers the basic
data analytical skills for analysing health data. Topics include: the elementary theory
of probability; diagnostic tests; data exploration and presentation; theoretical and
empirical distributions; measures of central tendency and dispersion; basic principles
of statistical inference; principles of hypothesis tests; confidence intervals; common
bivariate statistical tests; linear correlation and regression; and multiple linear
regression. Theory is complemented by the use of applied examples and exercises to
enhance understanding and facilitate development of practical skills. Being able to
read and evaluate health literature is essential for health professionals, especially
those in public health. Some computer literacy is assumed (e.g. Windows, Word, Excel).
Students will be introduced to the statistical software package, SPSS (IBM SPSS, Chicago,
Illinois). Numeracy skills are essential for the successful completion of this subject.
- critically engage with the conduct and interpretation of research in public health
and tropical medicine using fundamental biostatistical principles;
- integrate theoretical and technical biostatistical knowledge to recognise, manage,
describe and summarise data using the appropriate graphical and numerical methods;
- demonstrate expertise and judgement to identify the appropriate statistical inferential
methods for research questions in public health and tropical medicine, and make appropriate
use of the statistical software SPSS;
- work collaboratively, cooperatively and ethically within a team in the design, data
collection, analysis, interpretation, and reporting of an identified research question(s)
in public health and tropical medicine.
- quizzes or tests (50%)
- assignments (50%).
Special Assessment Requirements
Student must pass exam to pass subject
Study Period 5
|Census Date 07-May-2020
|Non-standard start/end 23-Mar-2020 to 19-Jun-2020
|Face to face teaching
23-Mar-2020 to 03-Apr-2020 (Please note early start date)
The student workload for this
credit point subject is approximately
- 60 hours lectures
- assessment and self-directed study
Study Period 2
|Census Date 27-Aug-2020
||Dr Iyke Emeto, Dr Daniel Lindsay
||Dr Iyke Emeto, Dr Daniel Lindsay, Assoc. Professor Kerrianne Watt.
- 130 hours - Self directed online learning and assessment
|Method of Delivery:
Minor variations might occur due to the continuous Subject quality improvement process,
and in case
of minor variation(s) in assessment details, the Subject Outline represents the latest