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Sampling error, caused by a small sample size, can be minimized by using a larger sample and is distinct from bias error.
Sampling error, which arises due to a small sample size, is the error that occurs when the sample does not represent the whole population accurately. This error can be reduced by increasing the sample size. It is different from bias error, which occurs when the sampling method is not random.
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