Answer:
Explanation:
There are four methods of sampling namely Random sampling,Stratified sampling, Cluster sampling and Multistage sampling. Let’s look at them one by one.
Random sampling - When each subject of the population is equally likely to be included in the sample, the sampling method is called random sampling.
Stratified sampling- Under this, the data are first divided into stratas. Each stratum consists of homogeneous subjects and strata are heterogeneous among themselves. Samples are randomly taken from each strata. Example- In an investigation of mortality rate of the insured, we can first subdivide the data into males and females and then take sample from each group. Here, male and female groups represent stratas.
Cluster sampling- Under this we first divide the data into clusters that are homogeneous among themselves and then select few of them and sample all observations from the randomly selected clusters. For example- suppose we want to take a sample of people's weight in a specific city. We observed that the areas in that city are similar to each other , so instead of travelling to each area and collecting data we can select few areas and then take observations from all people of those areas.
Multistage sampling - This adds one more stage to cluster sampling. Unlike cluster sampling where we sample all observations from the selected clusters, In multistage sampling we randomly sample observations from each selected cluster.
I hope this helped.