What is sampling?
Sampling is a technique which is used to select a portion of the population to represent the population.
Sampling techniques
Probability Sampling:
Probability sampling is randomly choosing the samples based on few criteria and every individual has a chance of being selected.
1) Simple Random
Simple Random is done by selecting the samples randomly. So, every individual has a chance of being selected.
Advantage is cost effective, simple and quick process. Disadvantage is, it is time consuming and the sample size may be huge.
2) Systematic
In systematic sampling method, the samples are selected systematically. The first sample is selected randomly and from that the nth sample is selected. It is cost and time effective and the sample is selected across the population.
3) Stratified
In stratified sampling method the entire population is divided into subgroups based on some criteria like age, height etc.
Then by using simple random or systematic sampling samples are selected from all subgroups equally. So, the population is represented properly.
4) Cluster
In cluster sampling the entire population is divided into subgroups based on some criteria. But unlike the stratified sampling, samples are not selected from all subgroups. Instead entire subgroups with same criteria are selected randomly.
Non- Probability Sampling:
In Non- Probability Sampling, samples are not selected based on any criteria. Every individual in the population does not get a chance of being selected.
1) Convenience
In convenience sampling, samples which are easily available for the researcher is selected. It does not represent the entire population.
2) Quota
Here the population is divided into multiple quotas and samples are selected from each quota.
3) Judgment
The researcher selects the samples based on some judgment or based on the researcher’s knowledge.
4) Snowball
In snowball sampling method, samples are selected from existing samples.
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