If you're conducting research, you might have heard about different sampling techniques. Sampling techniques help researchers select a subset of a population to gather data from. In this post, we'll explore the different types of sampling techniques and answer seven common questions.
Sampling techniques refer to the methods used by researchers to select a subset of a population (a sample) that can represent the entire population. These techniques are crucial in research as they help to reduce bias and ensure that the findings of the research can be generalized.
Probability sampling techniques are the ones where each member of the population has an equal chance of getting selected for the sample. Researchers use these methods because they help in ensuring that the sample is representative of the entire population. Some examples of probability sampling include simple random sampling, systematic random sampling, and stratified random sampling.
Non-probability sampling does not involve equal chances for all members in the population to be selected in a sample. Instead, researchers use other criteria such as convenience, judgement, or quota to select participants. Some examples include convenience sampling, purposive or judgmental sampling, snowball or chain referral sampling.
Convenience sampling is a type of non-probability sampling method where researchers use participants who are accessible and readily available for the study. In this method, participants are usually chosen based on their proximity or availability.
Stratified random sampling is a type of probability sampling method that stratifies or divides a population into homogenous groups called strata before selecting samples from each stratum. Researchers use this technique to ensure that each stratum is adequately represented in the sample.
Cluster sampling involves selecting groups from a population instead of individual members. This technique is usually used when the population is very large, and it's not possible to sample every member of the population. Researchers select clusters from the population, and then they choose samples from each cluster.
Sampling techniques are instrumental in conducting research, and researchers need to choose the right sampling technique for their study. Probability sampling techniques are ideal for ensuring that a sample is representative of the entire population, whereas non-probability sampling techniques are useful when probability sampling techniques cannot be used.
