Reproducibility
The ability to obtain consistent results using the same data, methods, and analysis.
Reproducibility concerns whether an analysis can produce consistent computational results using the same data, steps, methods, code, and conditions. Replication asks whether a new study using new data reaches compatible findings. Disciplines sometimes use these terms differently, so an article or study should state its definitions explicitly.
Clear records let others inspect how a result was produced, find mistakes, and build on useful work. Reproducible analysis benefits from documented data provenance, versioned code, named software and dependencies, and an explanation of any exclusions or transformations. Sensitive or restricted data may require controlled access rather than public release.
A matching result does not prove every assumption or interpretation is correct. A different result can arise from a real contextual difference, limited statistical power, measurement choices, or an error; it does not by itself settle which explanation is right. Compare methods and uncertainty, and treat replication as one contribution to a cumulative body of evidence.
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