Question

define stratified sampling. give an example of when stratified sampling is preferred.

Explanation:

Stratified sampling is a sampling method where the population is divided into non - overlapping subgroups (strata) based on certain characteristics. Samples are then randomly selected from each stratum in proportion to their size in the population. It is preferred when the population has distinct subgroups with different characteristics and we want to ensure representation from each subgroup. For example, in a survey about student satisfaction in a university with undergraduate and graduate students having different experiences, stratified sampling can be used. We can divide the student population into undergraduate and graduate strata and sample from each stratum to get a more accurate picture of overall student satisfaction.

Answer:

Stratified sampling is a sampling method where the population is partitioned into non - overlapping subgroups (strata) and samples are randomly drawn from each stratum in proportion to their size in the population. An example of when it is preferred is in a university student satisfaction survey, dividing students into undergraduate and graduate strata to ensure representation from both groups.