Fibre Testing & Bale Management

HVI Replicate & Outlier Checker

Deleting the odd reading fixes one cause and hides the other two.

Replicate Set This specimen batch
units
units
units
Instrument & Method Control references
units
units
units

Grubbs Statistic G

— σ

Compare against the tabulated critical value for this replicate count and alpha

Three Independent Checks

Maximum G Possible at This n
— σ
G as a Share of That Ceiling
— %
Standard Error of the Mean
— units
Replicate CV
— %
Check Cotton Drift vs Allowed Bias
— ×
Replicate SD vs Method Repeatability
— ×

G is a statistic, not a verdict: it must be compared against the tabulated Grubbs critical value for the replicate count and significance level in use — at n = 8 that is about 2.13 at 5% and 2.27 at 1%. The ceiling shown is a hard algebraic limit, (n−1)/√n, and no single value in a set can exceed it; a computed G above the ceiling means the suspect reading was not part of the set that produced the mean and standard deviation, which is itself a finding. Grubbs assumes an otherwise normal population and tests one outlier only, so applying it repeatedly to strip successive extremes progressively destroys the very distribution it relies on. Above all, a statistical outlier is not a licence to delete data. A reading may be extreme because the specimen genuinely was — contamination, a seed-coat fragment, a different growth — and discarding it because it is inconvenient converts a measurement into an opinion. Record every excluded value and the physical reason for excluding it.

HVI Replicate & Outlier Checker — free, with the formula and a worked example, at Textile School.