What is necessary for a hypothesis test to be valid?

For a hypothesis test to be valid, it is essential that there are clear definitions of the null and alternative hypotheses. This clarity allows researchers to precisely articulate what they are testing and what outcomes would lead them to reject or fail to reject the null hypothesis. A well-defined null hypothesis represents a statement of no effect or no difference, while the alternative hypothesis encapsulates what the researchers aim to prove. Without these clear definitions, the testing process loses focus and cannot yield meaningful conclusions.

While considerations like sample size, distribution, and sample selection are important factors that can affect the test's power and validity, the fundamental requirement for conducting a hypothesis test hinges on properly established hypotheses. The hypotheses serve as the foundation for statistical reasoning, setting the stage for the analysis and interpretation of results.