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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.
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Sampling Error It is the difference between the value of the actual population parameter and the sample statistic. Samples are used to arrive at conclusions regarding the p
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Stratified Random Sampling: This method of sampling is used when the population is comprised of natural subdivision of units, The method consist in classifying the population u
Review the Learning Resources and the media programs related to t tests. For additional support, review the Skill Builder: Research Design and Statistical Design and the Skill Buil
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