Sampling control
Sampling control is a method used in statistics to ensure that data collected for a study is representative of the population being studied. This is important because if the sample is not representative, the conclusions drawn from the study may not be accurate.
There are several techniques that can be used for sampling control, including random sampling, stratified sampling, and cluster sampling. Random sampling involves selecting individuals from the population at random, while stratified sampling involves dividing the population into subgroups and then selecting individuals from each subgroup. Cluster sampling involves dividing the population into clusters and then selecting entire clusters to be part of the sample.
For example, if a researcher is studying the eating habits of people in a particular city, they may use random sampling to select individuals from the city’s population. This ensures that the sample is representative of the entire population of the city, rather than just a specific group of people.
Sampling control is essential in ensuring the validity of research studies and the accuracy of the conclusions drawn from them.
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