How many samples do you need to be 95-percent confident that at least 95 percent—or even 99 percent—of your product is good? The answer depends on the type of response variable you are using—categorical or continuous.

The type of response will dictate whether you’ll use:
1. Attribute sampling: Determine the sample size for a categorical response that classifies each unit as good or bad (or perhaps, in spec or out of spec).
2. Variables sampling: Determine the sample size for a continuous measurement that follows a normal distribution.

The attribute sampling approach is valid regardless of the underlying distribution of the data. The variables sampling approach has a strict normality assumption but requires fewer samples. I’ll focus here on the attribute approach.

Attribute sampling

A simple formula gives you the sample size required to make a 95-percent confidence statement about the probability an item will be in spec when your sample of size n has zero defects.

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