Heteroskedasticity and Correlations Across Errors
... OLS is not BLUE. What more can we say? OLS estimates remain unbiased We only need Assumptions 1-3 to show that the OLS estimator is unbiased, hence a violation of Assumption 4 has no effect on this property The OLS estimator is no longer the best (minimum variance) linear unbiased estimator Serial c ...
... OLS is not BLUE. What more can we say? OLS estimates remain unbiased We only need Assumptions 1-3 to show that the OLS estimator is unbiased, hence a violation of Assumption 4 has no effect on this property The OLS estimator is no longer the best (minimum variance) linear unbiased estimator Serial c ...
Q. 1 – Q. 5 carry one mark each.
... It takes 10 s and 15 s, respectively, for two trains travelling at different constant speeds to completely pass a telegraph post. The length of the first train is 120 m and that of the second train is 150 m. The magnitude of the difference in the speeds of the two trains (in m/s) is ____________. (A ...
... It takes 10 s and 15 s, respectively, for two trains travelling at different constant speeds to completely pass a telegraph post. The length of the first train is 120 m and that of the second train is 150 m. The magnitude of the difference in the speeds of the two trains (in m/s) is ____________. (A ...
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... The larger the sample size, the shorter the confidence interval. This is because the larger the sample size, the smaller the standard error of the sample mean, which means the margin of error of the estimation is smaller. The larger the standard deviation of the population, the longer the confid ...
... The larger the sample size, the shorter the confidence interval. This is because the larger the sample size, the smaller the standard error of the sample mean, which means the margin of error of the estimation is smaller. The larger the standard deviation of the population, the longer the confid ...
CORK1 - University of Strathclyde
... hold exactly true for any (finite sized) sample of observations. (This is to be contrasted with asymptotic or ‘large sample’ results which are properties that are true only in a special, limiting case in which the sample size is infinitely large. These will be introduced later.) ...
... hold exactly true for any (finite sized) sample of observations. (This is to be contrasted with asymptotic or ‘large sample’ results which are properties that are true only in a special, limiting case in which the sample size is infinitely large. These will be introduced later.) ...
German tank problem
In the statistical theory of estimation, the problem of estimating the maximum of a discrete uniform distribution from sampling without replacement is known in English as the German tank problem, due to its application in World War II to the estimation of the number of German tanks.The analyses illustrate the difference between frequentist inference and Bayesian inference.Estimating the population maximum based on a single sample yields divergent results, while the estimation based on multiple samples is an instructive practical estimation question whose answer is simple but not obvious.