Hypothesis testing frameworks

Hypothesis testing frameworks are systematic methods used to determine whether a claim or assumption about a population is supported by data. You start with a null hypothesis (no effect or difference) and an alternative hypothesis (there is an effect). By analyzing sample data, we assess how likely it is to observe such results if the null hypothesis is true. If the data is unlikely under the null, we reject it in favor of the alternative. This process helps make informed decisions in research, quality control, and various fields, balancing evidence against uncertainty.