# Stratified sampling without sampling

At school we talked about stratified sampling regarding scientific studies.

I thought of a similar case:
Let's assume you have 4 questions for a certain number of people. Each of those people should only given one randomly chosen question. That leads to 4 groups of people, specified by the question they were asked.

Let's assume next that you want all of those groups to have the same age on average (you know the age of each person). I would sort them by age, split in 4 groups and then assign them randomly to another 4 groups one by one. So each of those 4 target groups have the same number of people from the source groups.

So you can divide a certain amount of entities with a known property to a certain amount of groups, all having nearly the same average property value.

My question:
Is this some kind of stratified sampling (granded, you're not doing the 'sample'-part), or is it a fully different procedure, and if so does it have a name?

• I believe you are referring to stratification: en.m.wikipedia.org/wiki/Stratification_(clinical_trials) Sep 14, 2017 at 17:01
• What you are doing is allocation rather than sampling so if you wanted a separate term for it you could call it stratified allocation or, depending on how you did it, randomised blocks allocation. The link in @FransRodenburg explains the usual context for this. Sep 15, 2017 at 12:12