Definition of 'Sampling'
There are two main types of sampling: probability sampling and non-probability sampling.
* **Probability sampling** is a type of sampling in which each member of the population has an equal chance of being selected. There are several different types of probability sampling, including simple random sampling, stratified random sampling, and cluster sampling.
* **Non-probability sampling** is a type of sampling in which not all members of the population have an equal chance of being selected. There are several different types of non-probability sampling, including convenience sampling, quota sampling, and snowball sampling.
The type of sampling method used depends on the specific needs of the study. Probability sampling is generally considered to be more accurate than non-probability sampling, but it can be more difficult and expensive to implement.
Once a sampling method has been selected, the next step is to determine the sample size. The sample size is the number of individuals or items that will be included in the sample. The sample size should be large enough to be representative of the population, but not so large that it becomes too expensive or time-consuming to collect the data.
After the sample has been collected, the data can be analyzed to draw conclusions about the population. The results of the analysis should be interpreted with caution, as they are only valid for the population from which the sample was drawn.
Sampling is an important statistical technique that is used in a variety of research studies. By using sampling, researchers can collect data from a large population without having to collect data from every individual in the population. This can save time and money, and it can also help to ensure that the results of the study are accurate.
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