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Methods for estimating the coefficients in the simple linear regression model are investigated. The least squares method is a purely mathematical approach, requiring no statistical assumptions other…
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This lesson reviews point estimation from a frequentist perspective. Method of moments and maximum likelihood methods are reviewed. Following that is a discussion of decision theory, optimal…
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In the previous lesson on best unbiased estimators and the Cramer-Rao Lower Bound, the concept of sufficiency was not used. We will now consider how sufficiency is a powerful tool in our search for…
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As we saw in the previous lesson, a comparison of estimators based on the mean squared error (MSE) may not yield a clear favorite. It turns out there is no "one best MSE" estimator. The…
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When a random sample is drawn, some summary of the values is usually computed. Any well-defined summary may be expressed mathematically as a function of an n-dimension vector. The domain of that…
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