## 2.6 Stratified sampling

In **stratified sampling**,
the population is split into a small number of large (usually homogeneous) groups called *strata*,
then cases are selected using a *simple random sample* from *each* stratum.

The strata must be unrelated to the variables.

For example,
if the RQ is about comparing the percentage of females and males who wear hats at midday,
a *stratified sample* of size 100 is **not** obtained by selecting 50 females and 50 males, for example.
This is merely selecting people from each level of the explanatory variable.

**Example 2.6 (Stratified sampling) **To select students in a large course at a particular university,
20 of the females and 20 of the males could be selected.
The sample is stratified by *sex* of the person.

The animation below shows how a stratified random sample of size 40 might be selected, by randomly selecting 20 female and 20 male students.

Similarly, the second animation below shows how a stratified random sample of size 40 might be selected, by randomly selecting 27 female and 13 male students.