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Stratified sampling is used where the population to be sampled can be divided into subsets, called strata, according to some criterion. Each of these strata are then treated as population and random samples representing the same sampling proportion are taken from each stratum. This ensures that in the overall sample, the number from each stratum is proportional to the size of the stratum in the population.
So, for example, if the population consists of 100 boys and 150 girls and you want a sample of 25.
The overall sampling proportion is 25/(100+150) = 25/250 = 1/10.
So the sampling procedure is to take a simple random sample of 10 boys out of 100 and a simple random sample of 15 girls out of 150.
If the whole sample were selected randomly, there is only a 17% probability that it would have been 10 boys and 15 girls. Stratification ensures both genders are represented proportionally in the sample.
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What is stratified random sampling?
cheese
What are the various kind of sampling?
They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.
Breifly explain three different examples of sampling?
simple random, stratified sampling, cluster sampling
What are the differences between systematic and stratified sampling?
Nothing! there the same
What are the advantages of systematic sampling as compared to stratified?
You can't conduct startified sampling if there are no difinative groups, thus systematic sampling is more efficient if your data has no groups.
