Method Validation: Accuracy, Precision, Recovery and Robustness
A method is not finished when it produces numbers. Validation is the evidence that the numbers are right, repeatable by someone else, unaffected by small changes, and correct on a sample of known content.
What a learner can do afterwards
- Separates accuracy from precision and names the experiment that tests each
- Designs a spike and recovery experiment and states what a recovery outside the accepted range implies
- Distinguishes repeatability from reproducibility and explains why both are reported
- Plans a robustness check by varying one method parameter at a time and reading the effect
1 · Read
You already know how to run a method and read a number. Validation asks whether the number deserves trust. Accuracy is closeness to the truth, tested on a sample of known content. Precision is repeatability, tested by running repeats and watching the spread.
You spike a blank sample with 10 mg and the method finds 7.8 mg, a recovery of 78 per cent. The accepted range depends on how much analyte is present: AOAC guidance expects 98 to 102 per cent for major components, widening to 80 to 110 per cent near 1 ppm. So 78 per cent fails at every level down to 1 ppm. The repeats agree closely, so the method is precise but biased. To find where the loss happens, spike one portion before extraction and one after: if only the early spike comes back low, the extraction is losing it.
Repeatability means the same hands in the same lab agree. Reproducibility means a different lab agrees too. Both are reported because a method that only works for its inventor is not finished.
Check robustness by varying one method parameter at a time, such as temperature or pH, and reading the effect. Small deliberate changes should barely move the result, or everyday wobble will ruin it.
Accuracy needs known samples, precision needs repeats, other labs must agree, and small changes must not matter.
2 · Watch
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8 questions wait behind this lesson, each with its answer explained. Every answer feeds the sky: stars light as they are learned, and dim when it is time to come back.