Residual: the difference between observed value and predicted/estimated value.
Error: the difference btw the observed value and the real value (which is usually unobservable)
MSE (Mean square error): the E[(X-X')^2], where X' is the real value of X.
Standard deviation: square root of the mean squared deviation. eg. sqrt(E[(Xi-u)^2]). It's square root of variance (see below)
Variance: a measurement of the dispersion for a set of numbers/observations (e.g. how far they are spread out from each other). If they have a mean, then variance is defined as E[(Xi-u)^2], where u is E(X). It's square of standard deviation.
Variance: a measurement of the dispersion for a set of numbers/observations (e.g. how far they are spread out from each other). If they have a mean, then variance is defined as E[(Xi-u)^2], where u is E(X). It's square of standard deviation.
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