Attribute sampling and variable sampling are commonly confused terms.
In attribute sampling, data is in the “attribute” form, and the result either conforms or does not conform.
It is a method of measuring quality that consists of noting the presence or absence of some characteristic (attribute) in each of the units under consideration.
Attribute sampling checks whether an item is defective or not. It’s a yes or no answer.
In variable sampling, data is in the “variable” form, and the result is rated on a continuous scale that measures the degree of conformity.
Variable sampling is about checking “how much”, “how good”, or “how bad”.
Let’s say you need to provide the average adult male and female height by country. Obviously you cannot measure the height of every adult in every country. So, you’ll take a sample of males and females from each country, measure their height and provide the statistics. The actual height of adults in that sample would be variable data, but whether an adult is above 6 ft tall or not, is attribute data.
A company manufactures premium glassware. The products are sold in lots of 1,000 items. The quality inspector randomly picks 50 items from each lot. If the inspector finds 2 or more broken or scratched items in the sample, the entire lot is rejected. This is an example of attribute sampling.
At an automobile manufacturing plant, if you are checking whether cars starts in first attempt or not, you are collecting attribute data, but if you are measuring the mileage of cars per liter of gasoline, you are collecting variable data.
Is the color black or not, is attribute data. What shade of gray it is, is variable data.