(2) Why OLS? The OLS method has been used popularly in regression analysis. The
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(2) Why OLS? The OLS method has been used popularly in regression analysis. The well-known Gauss-Markov theorem theoretically justifies that the OLS estimators possess many desirable statistically properties. Given the assumptions of the CLRM, an estimator B (the estimated slope coefficient from the sample) is said to be a BLUE of (the true slope coefficient fromthe population) if the following hold: 1. It is linear a. It is a linear function of a random variable Y in the regression model. 2. It is unbiased. a. Its average or expected value, E, is equal to the true value, 2. 3. It has minimum variance in the class of all such linear unbiased estimators a. An unbiased estimator with the least variance is known as an efficient estimator.Explanation / Answer
The assumption of the CLRM model.
The slope coefficient is blue if
3-It has minimum variance in the class of all such linear unbiased estimator.
An unbiased estimator with least variance will be blue.
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