significance test

In statistics, a significance test determines if an observed result from data is due to inherent qualities or random variance. A result is considered statistically significant if it has a very low probability of occurring by chance, assuming a null hypothesis (a claim of no difference or relationship) is true.1

This is assessed using hypothesis testing. A statistical test produces a p-value, representing the probability of the observation occurring if the null hypothesis is true. If this p-value is lower than a predetermined significance level (alpha, often 0.05), the null hypothesis is rejected, and the result is deemed statistically significant. Statistical significance indicates a difference is unlikely due to chance but doesn't necessarily imply the outcome's size or practical importance.12