Give an Account of Biased and Unbiased Estimators in Sampling

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The Answer is Statisticians develop many types of estimators, and from a theoretical as well as a practical perspective, it is important that they "truly estimate" the population parameters they are supposed to estimate. Suppose that we perform an experiment in which we repeatedly sampled from a population and computed a point estimate for a population parameter. Each individual point estimate will vary from the population parameter; however, we would hope that the long- term average expected value) of all possible point estimates would equal the population parameter. If the expected value of an estimator equals the population parameter it is intended to estimate, the estimator is said to be unbiased. If this is not True, the estimator is called biased and will not provide correct results.

Give an Account of Biased and Unbiased Estimators in Sampling

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Give an Account of Biased and Unbiased Estimators in Sampling

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Correct Answer:VerifiedShow Answer

Correct Answer:
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