The objective of this course is to develop skills and confidence in extracting meaning from data.
Health practice and research both inform and are informed by the evidence base, much of which is represented by quantitative summaries, figures, models and statistical tests. It is important to be able to critically evaluate existing evidence for it's relevance to a current situation yet the skills or knowledge needed to do that aren't always included in our professional training.
This course will place emphasis on interpreting the results of statistical summaries and tests in the context of health and the health system. In addition to summary statistics, data visualisation, correlation and model coefficients, we will investigate just what statistical significance does and doesn't mean. We will then move on to the pros and cons of categorising continuous measurements, the development and use of reference values, and the key things to think about in a meta-analysis. A plethora of tools, devices, algorithms, and scores exist in health, with more added every day, so we will introduce how to assess their performance, enabling critical evaluation of their suitability to a given situation. Throughout, we will use iNZight software to support your learning. You do not need to have used statistical software before.