Question

What are the principal differences and similarities between the major categories of probability sampling: simple random sampling, systematic sampling, stratified sampling, and cluster sampling? Provide an example of each type of sampling method.

Answer 1

Solution:

simple random sampling

In the Simple random sampling is a sampling where each and every item in the population has an equal chance to the selected in the sample.

e,g selection of one student in a whole class without any condition

systematic sampling

Systematic sampling it is technique which is used in sampling method in which sample members from a larger population are selected according to a random starting point but with a fixed, periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size.

e.e Deleting the every 10^th observation from data

stratified sampling

Stratified sampling is a sampling method . in this stratified sampling, the researcher divides the population into separate groups, called strata. Then, a probability sample (often a simple random sample ) is drawn from each group.

e.g divide all the employ in some equal group and then select employ from each group at randomly

cluster sampling

Cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population

e.g we divide the fruit like banana apple sapota and then select one of them either apple or banana or sapota or banana and sapota or apple and banana

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