A priori (literally: ‘from the former’) hypotheses are those based on assumed principles and deductions from the conclusions of previous research, and are generated prior to a new study taking place. They form a typical part of the scientific method, leading to the design of experimental studies and evidence syntheses to test and refine these new useful hypotheses. Statistical analyses to test hypotheses (see hypothesis testing) generally have more credibility when they are planned prospectively, in advance of the collection of the data. A priori hypotheses are distinct from a posteriori hypotheses, which are generated after relevant observations have been made. A priori probabilities and probability distributions are important in Bayesian analyses where they represent expectations of a certain quantity such as the relative effectiveness of an intervention, which may then be integrated with the observations of that quantity in a study to provide an improved, updated estimate a posteriori.
How to cite: A Priori (Tests) [online]. (2016). York; York Health Economics Consortium; 2016. https://yhec.co.uk/glossary/a-posteriori-tests/