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Stratified Sampling
Stratified Sampling is generally used when the population is heterogeneous. In this case, the population is first subdivided into several parts (or small groups) called strata. According to some relevant characteristics so that each stratum is more or less homogeneous. Each stratum is called a sub-population. Then a small sample (called sub-sample) is selected from each stratum at random. All the sub-samples combined together form the Stratified Sample. This represents the population properly. The process of obtaining and examining a Stratified Sample with a view to estimate the characteristic of the population is known as Stratified Sampling.
Example
The retailer can use Stratified Sampling as explained below:
She would analyze the bill copies according to items purchased, viz. TVs, Stereos, VCRs, etc. Each product’s customers would form a strata. Hence, we would have the following strata:
TV buyers
Stereo buyers
VCR buyers
For each stratum, random sampling would be done.
Advantages It is especially useful in case of open-end classes since only the position and not the values of items must be known. The median is also recommended if th
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