Estimator
In Data Science, an estimator is a statistical model that is used to estimate an unknown parameter of the population from a sample of data. It is a function that maps the data to an estimate of the parameter. Estimators can be used for a variety of purposes, such as hypothesis testing, confidence interval estimation, and prediction. The quality of an estimator is typically measured by its bias and variance. A biased estimator consistently overestimates or underestimates the true value of the parameter, while a high variance estimator is sensitive to small fluctuations in the data and can produce widely varying estimates. The goal is to find an estimator that has low bias and low variance, which is known as a consistent estimator.
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