On Campus
1 x 2-hour lecture fortnightly
1 x 2-hour workshop fortnightly
1 x 111-hour independent study per semester

Distance Online
1 x 2-hour online lecture fortnightly
1 x 2-hour online tutorial fortnightly
1 x 111-hour independent study per semester
Assignment(s), Analysis, Quizzes
Topic description

Within public health, there is a need for researchers, practitioners and policy makers to understand and interpret statistical findings from research. This topic is intended to meet the needs of those researchers wishing to gain knowledge of quantitative methods used in Public Health research. It is also designed to assist in meeting the core competencies for the Australasian Faculty of Public Health Medicine (AFPHM) for clinicians wishing to become Public Health Physicians. The focus of the topic is very applied and not mathematical.

Educational aims

This topic aims to give students an introduction to the discipline, an appreciation of a biostatistical perspective on information arising from the health arena and basic critical appraisal skills to assess the quality of research evidence. The topic introduces basic statistical concepts of data presentation, probability distributions, p values and confidence intervals, hypothesis testing, correlation and regression. Public health examples are used for demonstration. Students will practice preparing and interpreting data for published research.

Expected learning outcomes
On completion of this topic you will be expected to be able to:

  1. Classify data into appropriate measurement types
  2. Present data using relevant tables, graphical displays, and summary statistics, quantify uncertainty in study results
  3. Understand and explain the concepts of sampling and sampling distribution
  4. Formulate research hypotheses into a statistical context in public health studies
  5. Choose appropriate hypothesis tests to apply based on the type of data collected and the design of the study
  6. Understand the concept of correlation and regression
  7. Construct functioning scripted statistical analysis by using a specific software package R to load, wrangle, and analyse a dataset
  8. Demonstrate statistical reasoning skills correctly and contextually
  9. Critically assess the statistical methods and evidence presented in published research studies