Data considerations for Variables Acceptance Sampling (Create/Compare)

To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.

The sample should be selected randomly
The units to be inspected should be selected randomly and should be representative of all the items in the lot. This may require extra effort, such as numbering each item and drawing random numbers or stratifying the lot and sampling from each strata or layer. However, this process is necessary for the effectiveness of the sampling process.
The data must be continuous
Continuous data are measurements that may potentially be any numeric value within a range of values along a continuous scale, including fractional or decimal values. Common examples include measurements such as length, weight, and temperature.
Individual lots should be homogeneous
Lots represent the entire population of units that the sample will be taken from. Lots should be homogeneous. They should be packaged and shipped in sizes that are well-managed by both the consumer and supplier, and in a way that allows easy selection of samples. Inspecting larger lots is usually more economical than inspecting a series of smaller lots.
The consumer and supplier should agree on target quality levels
The consumer and supplier should agree to the highest defective rate that is acceptable (average quality level, AQL). The consumer and supplier should also agree to the highest defective rate that the consumer is willing to tolerate in an individual lot (rejectable quality level, RQL).
The AQL describes what the sampling plan will accept, and the RQL describes what the sampling plan will reject. You want to design a sampling plan that accepts a particular lot of product at the AQL most of the time, and rejects a particular lot of product at the RQL most of the time.
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