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What is a stratified random sample?
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.
Which is an effective use of stratified sampling?
Analyzing 20% of the items that are under $25,000
Why do you use Stratified sampling?
They have used Stratified Sample. Design because stratified sample is a sampling technique in which the researcher divided the entire target population into different subgroups, or strata, and then randomly selects the final subjects proportionally from the different strata. This type of sampling is used when the researcher wants to highlight specific subgroups within the population. So in this Research this technique is used by the researcher.
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
When do you need non-probability sampling?
There are at least two situations. Consider the situation where the population consists of a number of sub-populations (strata) such that units within a sub-population are similar to one another but there are much larger differences between units from different sub-populations. In order to ensure that the sample is representative, it may be sensible to use stratified random sampling. The sampling proportion may be a constant proportion or may even be such that the variance in each stratum is similar. The situation may also arise if the population is widely scattered geographically. Rather than expend time and money travelling all over the place, you could employ cluster sampling. Select a number of clusters of the population and then, within each cluster, carry out a census.
