On completion of this course students should be able to:
1. Demonstrate a broad understanding of statistical methods in evidence-based health care
2. Determine appropriate statistical methods of particular relevance to evidence-based health care in particular applications
3. Correctly employ these statistical methods and have the skills to effectively communicate with clinicians on the application of these methods and interpretation of the results

Using a series of case studies the various statistical methods relevant to clinical and diagnostic settings will be presented in a clinical context with appropriate practical interpretation. Students will learn to apply methods for assessment of clinical agreement, the statistical properties of diagnostic tests and their interpretation, statistical and ethical issues involved in screening tests, and the fundamentals of modelling for clinical prediction. Students will be actively engaged in an in-depth analysis of issues in systematic reviews of medical research studies, including selection and appraisal of studies, levels of evidence, meta-analytic methods for estimating effect sizes using fixed and random effect models, assessing heterogeneity and publication bias.

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Epidemiology (EPID6420);
Mathematical Background for Biostatistics (BIOS6040);
Probability and Distribution Theory (BIOS6170);
Principles of Statistical Inference (BIOS6050). This course may be taken concurrently with Clinical Biostatistics.

Distance Learning : Paper Based

Self Directed Learning

Self Directed Learning: for 6 hour(s) per Week for Full Term