When data is collected from a product sample randomly chosen from predefined groups, this is known as which type of sampling?

The correct choice is stratified sampling. This method involves dividing the population into distinct subgroups, or strata, that share similar characteristics. When data is collected from a product sample that is randomly selected from each of these predefined groups, it ensures that each subgroup is represented in the final sample. This approach helps to improve the accuracy and relevance of the results, as it captures the diversity within the entire population.

By using stratified sampling, researchers can obtain more precise estimates of the overall population characteristics because they account for the variations that exist within different strata. This kind of sampling is particularly useful when the subgroups are expected to be significantly different from each other regarding the variable of interest. It contrasts with simple sampling, where every individual has an equal chance of being chosen without considering any subgroup characteristics.