Basic concepts in hypothesis testing, including effect sizes, type I and type II errors, calculation of statistical power, non-centrality parameter, and applications of these concepts to twin studies.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is most often used by researchers to test predictions, called hypotheses. The first step in ...

The z test is a commonly used hypothesis test in inferential statistics that allows us to compare two populations using the mean values of samples from those populations, or to compare the mean of one ...

Figure 1. (click to enlarge) Effect of temperature on seal strength. The green bars represent samples created using low temperature. The orange indicates packages created using the high-temperature ...

Post-hoc testing is carried out after a statistical analysis where you have performed multiple significance tests, ‘post-hoc’ coming from the Latin “after this ...

The module is about core technologies underpinning modern artificial intelligence. The module will introduce statistical machine learning and probabilistic modelling and their application to ...