Abstract
Hypothesis testing is conceptually complex. It builds on a basic knowledge of probability, sampling distributions and the central limit theorem. It includes new concepts such as nuWaltemative hypothesis, alpha level, Type I and IT errors, power, sample size, statistical tests, critical value, p-value, observed value and decisions about hypotheses. The web of interrelationships between these concepts requires their holistic understanding for rational decision making. Firstly, this paper briefly summarises how these concepts may be linked together; and secondly, presents a methodology for research into what students know in these areas, their understanding of simple design concepts, and the sources of their difficulties with hypothesis testing.