MPH5041 · Introductory biostatistics

Overview

This unit introduces you 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. This includes 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).

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment in this unit includes hurdle assessment tasks. Failure of any hurdle assessment task may result in failure of the unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. Classify data into appropriate measurement types.
2. Present data using relevant tables, graphical displays, and summary statistics, quantify uncertainty in study results.
3. Formulate research hypotheses into a statistical context in public health studies.
4. Estimate quantities of interest and evaluate hypothesis with appropriate statistical methods.
5. Accurately interpret statistical methods and results reported in health publications.
6. Analyse data using a specific software package.

Workload

ONLINE mode: 2 hours online seminar (recorded), 2 hours online live tutorial, 2 hours online guided discussion, and 6 hours independent study per week. ON-CAMPUS mode: 4 face-to-face contact hours (2 hours seminar and 2 hours tutorial), + 2 hours online guided discussion, + 6 hours independent study per week.

Student experience, not official rules. Nothing here changes what the Handbook says.