Stratified Random Sampling

Stratified random sampling is a statistical sampling method used to ensure that the sample is representative of the population. It is a type of probability sampling, which means that each member of the population has a known and equal chance of being selected.

Stratified random sampling is used when the population is divided into different groups, or strata, based on a common characteristic. For example, a population of students could be divided into strata based on their grade level. Once the strata have been created, a random sample is taken from each stratum. This ensures that the sample is representative of the population as a whole, and that no one group is overrepresented or underrepresented.

Stratified random sampling is a more accurate and representative sampling method than simple random sampling. However, it is also more complex and time-consuming to implement.

Here are the steps involved in stratified random sampling:

1. The population is divided into different groups, or strata, based on a common characteristic. 2. A random sample is taken from each stratum. 3. The results from the individual strata are combined to create a representative sample of the population as a whole.

Stratified random sampling is used in a variety of applications, including:

• Market research
• Political polling
• Clinical trials
• Educational research

It is a valuable tool for researchers who want to ensure that their results are accurate and representative of the population they are studying.