Introduction
Data Validation independently checks whether an analysis is reliable. Starting from the question, sources, and metric definitions, it verifies filters, calculations, statistical methods, charts, citations, conclusions, and recommendations. It separates issues that invalidate the result from limitations that need disclosure and preserves the evidence behind each finding.
Use Cases
Use it before report publication, experiment acceptance, executive review, external research citation, or a consequential business decision. It can recalculate figures, test method fit, inspect chart fidelity, and catch claims that overstate correlation, estimates, or limited samples.
Template
Provide the question, data, code or calculations, charts, draft report, and cited sources. Define metrics, sample scope, method choices, and decision context. Add the conclusions that matter most, acceptable error, deadline, and whether you need an issue list, revisions, or a validation status.
