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Stratified random sampling is a sampling scheme which is used when the population comprises a number of strata, or subsets, which are similar within the strata but differ from one stratum to another. One example is school children stratified according to classes, or salaries stratified by departments.
A simple random sample may not have enough representatives from each stratum and the solution is to use stratified random sampling. Under this scheme, the overall sampling proportion (sample size/population size) is determined and a sample is drawn from each stratum which represents the same proportion.
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What is the difference between random and stratified sample in the survey method?
The main difference is that the way of selecting a sample Random sample purely on randomly selected sample,in random sample every objective has a an equal chance to get into sample but it may follow heterogeneous,to over come this problem we can use stratified Random Sample Here the difference is that random sample may follow heterogeneity and Stratified follows homogeneity
What is the difference between stratified and random sampling?
In a stratified sample, the sampling proportion is the same for each stratum. In a random sample it should be but, due to randomness, need not be.
What is the difference between a simple random sample and a stratified random sample?
Sometimes a population consists of a number of subsets (strata) such that members within any particular strata are alike while difference between strata are more than simply random variations. In such a case, the population can be split up into strata. Then a stratified random sample consists of simple random samples, with the same sampling proportion, taken within each stratum.
What is stratified random sampling in statistics?
Stratified Random Sampling: obtained by separating the population into mutually exclusive (only belong to one set) sets, or stratas, and then drawing simple random samples (a sample selected in a way that every possible sample with the same number of observation is equally likely to be chosen) from each stratum.
Is the best description of a stratified random sample?
Stratified random sampling is a form of probability sampling that provides a methodology for dividing a population into smaller subgroups as a means of ensuring greater accuracy of your high-level survey results. The smaller subgroups are called strata. Stratified random sampling is also called proportional or quota random sampling.
