Unbiasedness refers to the property of an estimator or an approximation method where the expected value of the estimate equals the true value of the parameter being estimated. This characteristic ensures that, on average, the estimates generated do not systematically overestimate or underestimate the target values, allowing for more reliable predictions. In the context of least squares approximation, unbiasedness plays a crucial role in ensuring that the fitted model accurately represents the underlying data without inherent bias.
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