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This subject provides the foundation theory and methods needed for biostatisticians to apply and critically interpret statistical inference, the science of drawing conclusions from data that are subject to variability. Major topics include review of the key concepts of estimation including sampling variability and construction of confidence intervals; null hypothesis testing; methods of inference based on likelihood theory (Fisher and observed information, likelihood ratio, Wald and score tests); and an introduction to the Bayesian approach to inference. The approach will emphasise a critical understand¬ing of the role of statistical inference in health research.
Intended learning outcomes
To provide a strong mathematical and conceptual foundation in the methods of statistical inference, with an emphasis on practical aspects of the interpretation and communication of statistically based conclusions in health research.
- Independent problem solving,
- Facility with abstract reasoning,
- Clarity of written expression,
- Sound communication of technical concepts
Last updated: 6 December 2019