Variables vs Attributes Sampling

Acceptance sampling plans come in two flavors: variables plans (measuring a continuous characteristic) and attributes plans (classifying items as conforming or not). Choosing the right type affects sample size, cost, and information gained.

Side-by-side comparison

	Variables sampling	Attributes sampling
Data type	Measurement (length, weight, voltage)	Count (pass/fail, defective/nondefective)
Standards	MIL-STD-414, ANSI/ASQ Z1.9	MIL-STD-105E, ANSI/ASQ Z1.4
Sample size	Smaller — more efficient	Larger — less efficient per unit of information
Information	How far from spec and distribution shape	Only whether item passes or fails
Assumption	Requires normality of the characteristic	No distribution assumption needed
Cost per unit	Higher (measurement takes more time)	Lower (go/no-go gauge is quick)

When to use variables sampling

Destructive testing where each unit is expensive
Tight specification where you need to estimate proportion out of spec
Process average monitoring (k method)

CQE exam tips

Variables plans require normality — if the distribution is non-normal, attributes plans are safer.
For a given AQL and protection, variables plans need roughly one-third to one-half the sample size of attributes plans.
ANSI/ASQ Z1.9 uses AQL just like Z1.4 — the AQL concept is the same; only the decision rule differs.

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