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What is simple random sampling and stratified random sampling?

yes


Which sampling method is based on probability?

There are many such methods: cluster sampling, stratified random sampling, simple random sampling.Their usefulness depends on the circumstances.


Mention different types of sampling in statistics.?

Simple Random Sample Stratified Random Sampling Cluster Sampling Systematic Sampling Convenience Sampling


Breifly explain three different examples of sampling?

simple random, stratified sampling, cluster sampling


What are the various kind of sampling?

They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.


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.


Example of stratified random sampling?

In stratified sampling, the population to be sampled is divided into groups (strata), and then a simple random sample from each strata is selected. For example, a state could be separated into counties, a school could be separated into grades. These would be the 'strata'.


What is the difference between simple random sampling and random sampling?

Simple!


When individuals all have an equal chance of being selected and all samples have an equal chance of being selected its called a stratified random example convenience cluster or simple random sample?

Simple random sampling.


Define the four different sampling techniques?

1) Simple random sampling 2) Systematic sampling 3) Stratified sampling 4) Cluster sampling 5) Probability proportional to size sampling 6) Matched random sampling 7) Quota sampling 8) Convenience sampling 9) Line-intercept sampling 10) Panel sampling


What is the difference between stratified random sampling and cluster sampling?

Basically in a stratified sampling procedure, the population is first partitioned into disjoint classes (the strata) which together are exhaustive. Thus each population element should be within one and only one stratum. Then a simple random sample is taken from each stratum, the sampling effort may either be a proportional allocation (each simple random sample would contain an amount of variates from a stratum which is proportional to the size of that stratum) or according to optimal allocation, where the target is to have a final sample with the minimum variabilty possible. The main difference between stratified and cluster sampling is that in stratified sampling all the strata need to be sampled. In cluster sampling one proceeds by first selecting a number of clusters at random and then sampling each cluster or conduct a census of each cluster. But usually not all clusters would be included.


Is cluster sampling random?

It can be but it is not simple random sampling.