A small p-value does not state how much a measured difference matters to the machinery decision.
Detection and importance are separate questions
Statistical significance relates to a specified test and its assumptions. Practical importance concerns the magnitude relevant to the intended engineering decision. A large sample can detect a difference too small to matter operationally, while a small sample can leave a practically important difference uncertain. Report the effect and its uncertainty with the test result.
A hypothetical supplier comparison
Suppose an illustrative comparison estimates a small change in a trial response and the test detects it. Before ranking offers, ask whether that magnitude would change the buyer’s approved requirement, operating outcome or cost. The test outcome alone does not supply that threshold.
Conversely, an imprecisely estimated large change cannot be dismissed merely because a test did not reject its null hypothesis. Retain the uncertainty and decide what additional evidence the equipment choice needs. These examples contain no HM performance or cost claims.
Agree the decision context before the analysis
Identify the characteristic, units, comparison and magnitude that would matter to the buyer. Explain the engineering basis of that magnitude rather than borrowing a percentage from an unrelated case. Keep the actual product requirement and decision rule separate from a statistical test threshold.
When reporting results, provide group definitions, effect estimate, relevant interval and model assumptions. If the data cannot distinguish a worthwhile change from an unimportant one, describe that uncertainty directly. This approach makes the statistical analysis serve the quotation or trial question instead of letting a single software label determine the machinery purchase.
Trial discussion worksheet
This blank worksheet is for your own project. It contains no H M machine trial result.
| Review question | Reference or observation to retain |
|---|---|
| What difference would matter? | Buyer’s engineering rationale |
| What effect was estimated? | Magnitude, unit and uncertainty |
| Which hypothesis was tested? | Specified test and assumptions |
Customer Questions
Does significance mean a large improvement?
No. It does not by itself describe practical magnitude.
Does non-significance prove equivalence?
No. The available evidence may simply be imprecise.
Should a practical threshold be selected after viewing results?
State and justify the decision context before using it to classify the result.
Primary References
These references support the technical principles discussed in this guide. The worked examples and review questions are educational.
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