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Bias and sampling error

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The concepts of bias and sampling error are often confused with each other and poorly understood, even among those who frequently do surveys. This is a shame because it results in much wasted effort and invalid conclusions. The following explanation attempts to clarify the situation.

To being with, the estimate from a survey is never exactly identical to the actual value in the population, even if all the procedures are done correctly. For example, in a hypothetical population in which precisely 50.0% of non-pregnant women of child-bearing age have anaemia, a very well-done survey of 500 women shows that 225 (45.0%) have anaemia.

Why might this be true? (Click here for answer.)