What do you understand by sampling? What are the two types of sampling? Name them. Explain in brief any one type of sampling.

 Sampling is the process of selecting a subset of individuals or units from a larger population in order to make inferences or draw conclusions about the population. Sampling is used in many fields, including statistics, social sciences, market research, and public health.

The two types of sampling are probability sampling and non-probability sampling. Probability sampling is a sampling method in which every individual or unit in the population has a known, nonzero probability of being selected for the sample. Non-probability sampling is a sampling method in which the selection of individuals or units for the sample is based on non-random criteria or subjective judgment.

Probability sampling methods include simple random sampling, stratified random sampling, cluster sampling, and systematic sampling. Non-probability sampling methods include convenience sampling, quota sampling, purposive sampling, and snowball sampling.

Simple random sampling is a type of probability sampling in which each individual or unit in the population has an equal chance of being selected for the sample. This is done by selecting individuals or units from the population at random, such as by using a random number generator. Simple random sampling is often used when the population is relatively small and homogeneous.

Stratified random sampling is a type of probability sampling in which the population is divided into strata or subgroups based on certain characteristics, and then individuals or units are randomly selected from each stratum to form the sample. Stratified random sampling is often used when the population is heterogeneous, and there are important subgroups that need to be represented in the sample.

Cluster sampling is a type of probability sampling in which the population is divided into clusters or groups, and then a random sample of clusters is selected. Individuals or units within the selected clusters are then sampled. Cluster sampling is often used when the population is large and spread out over a wide geographic area.

Systematic sampling is a type of probability sampling in which individuals or units are selected from the population at regular intervals, such as every nth individual or unit. Systematic sampling is often used when the population is large and there is a natural ordering to the individuals or units.

Convenience sampling is a type of non-probability sampling in which individuals or units are selected based on convenience or availability. Convenience sampling is often used when time, cost, or other constraints make it difficult to use other sampling methods. However, convenience sampling is subject to selection bias, as the individuals or units selected may not be representative of the population.

In conclusion, sampling is a crucial technique used in research to obtain insights and draw conclusions about a larger population. Probability sampling and non-probability sampling are the two types of sampling. Among the probability sampling methods, simple random sampling, stratified random sampling, cluster sampling, and systematic sampling are commonly used. Convenience sampling, quota sampling, purposive sampling, and snowball sampling are some of the non-probability sampling methods. The choice of sampling method depends on various factors, including the research question, the size and heterogeneity of the population, and available resources.

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