Question square sampling is like stratified sampling, but the idea is that entire groups are selected as opposed to individuals.

The correct answer is cluster sampling.<br /><br />Cluster sampling is a type of sampling method where the population is divided into mutually exclusive and exhaustive subgroups, called clusters. Then, a random sample of clusters is selected, and all individuals within the selected clusters are included in the sample.<br /><br />In cluster sampling, the entire groups or clusters are selected as opposed to individuals. This is different from stratified sampling, where the population is divided into subgroups based on certain characteristics, and then a random sample of individuals is selected from each subgroup.<br /><br />Cluster sampling is often used when it is more cost-effective or convenient to sample entire groups or clusters rather than individuals. For example, if a researcher wants to study the teaching methods of a particular school district, it may be more efficient to randomly select a few schools (clusters) and then include all teachers from those selected schools in the sample, rather than randomly selecting individual teachers from the entire district.<br /><br />Cluster sampling can be advantageous in terms of reducing costs and time, as it eliminates the need for a complete list of the population and allows for more efficient data collection. However, it may also introduce some bias if the selected clusters are not representative of the entire population.