3 x 2.5-hour independent studies weekly
2 x 1-hour on-line exercises weekly
1 x 1-hour on-line tutorial weekly
Assumed knowledge
No knowledge of statistics or epidemiological research is required although a reasonable level of basic numeracy skills are assumed.
Course context
Students must be admitted into a postgraduate course to enrol into the topic,
Assignment(s); Test(s)
Topic description
This topic is intended to meet the needs of those researchers wishing to gain knowledge of quantitative methods used in Epidemiological 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.
Educational aims
The overall aims of this topic are:

  • To provide health researchers with the knowledge required to understand the rationale behind the use of specific statistical tests used in health research.

  • To encourage health researchers to formulate their own statistically testable research hypotheses for quantitative health data.

  • To provide health researchers with the skills required to perform appropriate statistical tests in health research.

  • To assist in meeting the entrance requirements for Domain 3 (Information, Research and Evaluation) of the Australasian Faculty of Public Health Medicine (AFPHM) core competencies for clinicians wishing to become Public Health Physicians.

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

  1. Describe data appropriately using graphs and descriptive statistics. Use appropriate measures of central tendency and measures of dispersion for the given data.

  2. Accurately describe the normal and binomial probability distributions commonly used in biostatistics, and the central limit theorem. Understand what is meant by the null hypothesis and alternative hypothesis, p-values and confidence intervals.

  3. Perform sample size and power calculations for survey precision, the comparison of 2 proportions and the comparison of 2 means. Understand Type 1 and Type 2 error rates and the relationship between them.

  4. Know how to test for associations for continuous data using correlation coefficients, simple linear and multivariate linear regression.

  5. Perform appropriate tests of differences in means of normally distributed data between groups for independent and dependent samples.

  6. Accurately compare proportions for binary and categorical data.

  7. Know how to perform logistical regression, and interpret an odds ratio.

  8. Know how to compare rates using Poisson regression and interpret a hazard ration.