Statistical test selection connects a research question and study design to an analysis whose assumptions fit the outcome type, group structure, pairing, sample size, and intended inference. The same dataset can require different methods depending on whether the goal is comparison, association, prediction, or description.
Statistical Test Selector applies this concept to its defined inputs and workflow. It is a planning helper for choosing candidate tests before analysis.
The helper structures structured design notes and returns recommended test shortlist and assumption checklist so decisions and omissions can be reviewed explicitly. Input structure, labels, missing values, and selected options must match the intended workflow. It supports preparation and independent checking rather than replacing the governing software, standard, evidence, or professional review. The selector narrows candidates but does not validate the study design.