Explain the different non-random sampling method with examples
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Non-probability sampling is a sampling technique where the odds of any member being selected for a sample cannot be calculated. It’s the opposite of probability sampling, where you can calculate the odds. In addition, probability sampling involves random selection, while non-probability sampling does not–it relies on the subjective judgement of the researcher.A major advantage with non-probability sampling is that — compared to probability sampling — it’s very cost- and time-effective. It’s also easy to use and can also be used when it’s impossible to conduct probability sampling (e.g. when you have a very small population to work with).
One major disadvantage of non-probability sampling is that it’s impossible to know how well you are representing the population. Plus, you can’t calculate confidence intervals and margins of error. This is the major reason why, if at all possible, you should consider probability sampling methods first.
One major disadvantage of non-probability sampling is that it’s impossible to know how well you are representing the population. Plus, you can’t calculate confidence intervals and margins of error. This is the major reason why, if at all possible, you should consider probability sampling methods first.
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