Sampling variability
Sampling variability is the natural variation in a statistic from one random sample to the next, and it is variation rather than bias.
Two random samples from the same population almost never give the same value, so a sample statistic bounces around the parameter it estimates. For example, two random samples of 50 students from one school might give mean GPAs of 3.12 and 3.05 with nothing wrong in either sample. Sampling variability shrinks as the sample size grows, because the sampling distribution of the statistic gets narrower. Bias behaves differently: it is a systematic push in one direction, and a larger sample does not remove it.
Where this comes up
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