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Batch and measurement-process variation — Examples

1 · Prerequisites

2 · Summary

Three stable reference standards are measured on two days under stipulated linear response curves. The worked calculations recover the day-specific slopes, fit the equally weighted pooled line, and compare its check-standard residuals and inverse readings with the separate curves. The example is deterministic and illustrates how a shared curve can conceal day-specific behavior; it makes no empirical, inferential, or general stability claim.

3 · Logical flowchart

4 · Definitions, theorems and proofs

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5 · Examples, counterexamples and false statements

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Day-specific calibration slope drift and check standards

Example

Suppose the three stable reference standards have assigned quantities q∈{0,5,10}. Remeasure these same standards on two days, obtaining the stipulated exact response table

Reference quantity qDay 1 responseDay 2 response
011
51112
102123

Take [0,10] as the declared calibration range. The standards are check standards here: fixed reference artifacts measured again over time to reveal changes in the measurement process. The numbers are a deterministic illustration, not observed data. Fit one equally weighted straight line with an intercept to all six response pairs and compare it with the separate day-specific calibration curves.

Facts & Assumptions

Given: The assigned reference values and stipulated responses in the Example, with the pooled line defined to minimize the sum of squared vertical residuals over all six pairs.

[F1]

Measurands, calibration, and measurement uncertainty: a calibration curve is a specified relation between a reference quantity and instrument response used to convert a later response into a measurand estimate.

[F2]

Batch and measurement-process variation: day is a batch/process condition, and calibration curves are pooled only under an explicit shared curve or equivalence model.

[A1]

The three reference standards remain stable with assigned values 0,5,10 on both days, and the response table is stipulated exactly as shown.

[A2]

The pooled line is a+bq with a,b∈R, fitted by minimizing ∑d=12∑q∈{0,5,10}(rdq−a−bq)2 with equal weight for each of the six readings.

Verification

1.1givenA1algebra

The day-specific lines are r1(q)=1+2q and r2(q)=1+2.2q: each intercept is the response at q=0, and the slopes are (21−1)/10=2 and (23−1)/10=2.2. In particular the known standard at q=5 has responses 11 and 12.

1.2givenA1algebra

The six reference values have mean qˉ=5 and the six responses have mean rˉ=69/6=11.5. Their centered sums are Sqq=∑(q−qˉ)2=100 and Sqr=∑(q−qˉ)(r−rˉ)=210: the two q=0 readings contribute 105, the q=5 readings contribute 0, and the two q=10 readings contribute 105.

2.1givenA2step 1.2algebra

Write each residual as (r−rˉ)−b(q−qˉ)+(rˉ−a−bqˉ). The first two terms sum to zero over the six pairs, so expanding the sum of squared residuals gives ∑[(r−rˉ)−b(q−qˉ)]2+6(rˉ−a−bqˉ)2. For fixed b this is minimized at a=rˉ−bqˉ; the remaining slope-dependent terms are Sqqb2−2Sqrb, whose completed square is Sqq(b−Sqr/Sqq)2 plus a constant. Since Sqq=100>0, the unique minimizing slope is b=210/100=21/10 and a=11.5−(21/10)(5)=1, giving r^(q)=1+(21/10)q.

3.1F1F2A1step 1.1step 2.1algebra∎

At the q=5 check standard, the pooled line predicts 11.5, so its day-specific residuals are 11−11.5=−0.5 and 12−11.5=0.5. Inverting the pooled line maps the two observed responses to 10/(21/10)=100/21 and 11/(21/10)=110/21, whereas the separate day lines each map their own response back to q=5. The three-standard table exposes the differing slopes in this stipulated example; it supplies no empirical evidence, statistical test, or general justification for pooling calibration curves.

Remarks

There is one stipulated reading per standard per day, so the table does not estimate repeatability, a variance component, a control limit, or uncertainty. It only demonstrates the finite arithmetic of comparing three standard responses under two specified lines.

Sources