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    I've tried looking online but really complicated answers that are hard to understand are given.
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    If you mean the bias of an estimator, it is the difference between the expected value of the estimator and the true value of the underlying parameter.

    Say a population has a true mean, variance et cetera, and you want to estimate these by taking a finite sample from that population. An unbiased estimator is one where the estimate, on average, gives the true population statistic (although in reality the sample statistics will vary about this number).
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    (Original post by Rinsed)
    If you mean the bias of an estimator, it is the difference between the expected value of the estimator and the true value of the underlying parameter.

    Say a population has a true mean, variance et cetera, and you want to estimate these by taking a finite sample from that population. An unbiased estimator is one where the estimate, on average, gives the true population statistic (although in reality the sample statistics will vary about this number).
    thanks for the reply. so could I say that bias is a value that doesn't truly reflect the real population
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    (Original post by jonjoshelvey21)
    thanks for the reply. so could I say that bias is a value that doesn't truly reflect the real population
    If your estimator has a positive bias, say, then you expect your estimates to come out on average a bit higher than the true population parameter. Bias is a measure of how much you expect your estimator to differ from the underlying population.
 
 
 
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