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Stratified random sampling involves a method where the researcher divides a more extensive population into smaller groups that usually don’t overlap but represent the entire population. This sampling technique usually works around a large population and has its fair share of advantages and disadvantages. There are two ways in which researchers choose the samples in this method of sampling: The lottery system and using number generating software/ random number table. Finally, the numbers that are chosen are the members that are included in the sample. This sampling method is as easy as assigning numbers to the individuals (sample) and then randomly choosing from those numbers through an automated process. Simple random sampling, as the name suggests, is an entirely random method of selecting the sample. What are the types of probability sampling? Probability sampling uses statistical theory to randomly select a small group of people (sample) from an existing large population and then predict that all their responses will match the overall population. Probability sampling gives you the best chance to create a sample that is truly representative of the population.įrom the responses received, management will now be able to know whether employees in that organization are happy or not about the amendment. For example, if you have a population of 100 people, every person would have odds of 1 in 100 for getting selected. The most critical requirement of probability sampling is that everyone in your population has a known and equal chance of getting selected. For a participant to be considered as a probability sample, he/she must be selected using a random selection. Definition: Probability sampling is defined as a sampling technique in which the researcher chooses samples from a larger population using a method based on the theory of probability.