Statistical Hypothesis

Hypothesis testing in data mining is a method used to check whether assumptions about a dataset are likely to be true.

It involves starting with two statements: a null hypothesis (usually representing no effect or change) and an alternative hypothesis (representing the effect or change being tested).

Statistical tests like t-tests or ANOVA are then applied to compare groups or variables. The results are measured using p-values and confidence intervals, which help determine if the findings are statistically meaningful.