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'.
Simple Random Sample Stratified Random Sampling Cluster Sampling Systematic Sampling Convenience Sampling
There are many advantages of using the stratified random sampling. Some of them are, ability to reduce human potential in choosing the cases in sample, statistical conclusion fro data collected, improving representation of strata etc.
Simple random sampling.
You are correct; convenience sampling is not random sampling.
yes
No.
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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'.
There are many such methods: cluster sampling, stratified random sampling, simple random sampling.Their usefulness depends on the circumstances.
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Simple Random Sample Stratified Random Sampling Cluster Sampling Systematic Sampling Convenience 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.
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.
They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.
simple random, stratified sampling, cluster sampling
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.