Probability Sampling is a sampling technique in which sample from a larger population are chosen using a method based on the theory of probability. For a participant to be considered as a probability sample, he/she must be selected using a random selection.
Example of probability sampling: -
Consider hypothetically an organization has 7, 00,000 employees sitting at different geographic locations. The organization wishes to make certain amendment in its human resource policy, but before they roll out the change they wish to know if the employees will be happy with the change or not. However, it’s a tedious task to reach out to all 7, 00,000 employees. This is where probability sampling comes handy. A sample from the larger population i.e. from 7, 00,000 employees can be chosen. This sample will represent the population. A survey now can be deployed to the sample.
From the responses received, management will now be able to know whether employees in that organization are happy or not about the amendment.
Non-probability sampling is a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected.
For example:-
One person could have a 10% chance of being selected and another person could have a 50% chance of being selected. It’s non-probability sampling when you can’t calculate the odds at all.
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