# Question #6d8d4

Nov 22, 2017

Simple Random Sampling, as the name suggests is completely random i.e. selection of a sample is a matter of chance whereas in Stratified Sampling the universe is divided into groups.

#### Explanation:

In stratified sampling, the universe is divided into certain groups which are mutually exclusive and include all the items in the universe. A sample is then selected at random from each of these strata(groups).
Simple Random Sampling doesn't do this. It chooses samples randomly from the universe.
In this way, stratified sampling ensures that a more representative sample is chosen which is more accurate and thus balances the uncertainty of simple random sampling against bias of deliberate selection.

The simple random sampling method requires a larger sample as compared to stratified sample and thus involves more cost.

An example/application of Simple Random Sampling is Lotteries/Lucky Draw Contests.

Stratified Sampling is used for political surveys, market research of certain products eg. ice creams: the strata here would be different age groups and then a sample from each of the age groups would be selected for the survey.