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Stratified Sampling is a category under Probability sampling which is based on dividing a population into strata, and members for the sample are selected randomly from these strata.
In stratified sampling, the strata must be homogenous and also collectively exhaustive, and mutually exclusive as well. The strata must define a part of the population. Moreover, the members of the sample must be distinct, that is, every element must be a part of one and only one strata in the population. This implies that the entire population requires to be a part of the samples.
To ensure precision and reduce sampling error, simple random sampling is employed in each stratum.
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Often used in market research, Cluster Sampling, is a technique used when homogeneity is external but heterogeneity is internal within clusters/groupings. It is a process of dividing a population into multiple groups/clusters.
Cluster sampling is generally used to reduce the number of interviews and the cost, to reach the desired accuracy. When the majority of heterogeneity is internal within the group in fixed sample size, the chance of random error is reduced.
There are single-stage, two-stage, or multiple-stage sampling methods in cluster sampling. These methods depend upon the number of steps required to create the desired sample.
In Cluster Sampling, the total population is divided into clusters. A simple random sample of the cluster is chosen and the elements in each of these clusters are then sampled.
One-stage/Single-stage Cluster Sampling: In case when all elements in each cluster sample are sampled.
Two-stage Cluster Sampling: When from each of these clusters a simple random subsample of elements is chosen.
As mentioned cluster sampling is advantageous when a large population is in need of a survey because it is less costly. Hence, area sampling is one of the examples of Cluster Sampling. Also, it is used when high mortality cases like wars, famines and natural diseases are required for estimation.
In the process of cluster sampling, respondents are grouped within a local area into several clusters. However, it is also essential to achieve precision in the estimate for which sample size must be increased.
All the above information highlights the difference between the two categories of the Sampling. Underneath are some key difference to clear any lingering doubts
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