Which of the following describes the method of sampling in which elements of data are selected randomly from each of the small subgroups within a…

This is because stratified is a type of sampling in which elements of data are selected randomly from

each of the small subgroups within a population, such as age groups, gender groups, or income

groups. Stratified sampling can be used to ensure that the sample is representative and proportional

of the population, as well as reduce the sampling error or bias. For example, stratified sampling can

be used to select a sample of voters from different political parties based on their proportion in the

population. The other types of sampling are not the types of sampling in which elements of data are

selected randomly from each of the small subgroups within a population. Here is why:

Simple random is a type of sampling in which elements of data are selected randomly from the

entire population, without dividing it into any subgroups. Simple random sampling can be used to

ensure that every element in the population has an equal chance of being selected, as well as avoid

any systematic error or bias. For example, simple random sampling can be used to select a sample of

students from a school by using a lottery or a computer-generated number.

Cluster is a type of sampling in which elements of data are selected randomly from a few large

subgroups within a population, such as regions, districts, or schools. Cluster sampling can be used to

reduce the cost and complexity of sampling, as well as increase the feasibility and convenience of

sampling. For example, cluster sampling can be used to select a sample of households from a few

neighborhoods by using a map or a list.

Systematic is a type of sampling in which elements of data are selected at regular intervals from an

ordered list or sequence within a population, such as every nth element or every kth element.

Systematic sampling can be used to simplify and speed up the sampling process, as well as ensure

that the sample covers the entire range or scope of the population. For example, systematic

sampling can be used to select a sample of books from a library by using an alphabetical order or a

numerical order.