User talk:Holcombea
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- I think I'm interested in a different kind of answer. As I understand it, the expected value minimizes the *average* difference between the estimate and the actual unknown parameter value. But in other contexts, Bayesians may minimize the average sum of squared difference, and in maximum likelihood the mode of the posterior distribution is used. Did Laplace have any particular reason for choosing the mean? Is this somehow embedded in the law of total probability? Sorry if this is a naive question. Alex Holcombe 10:23, 15 October 2007 (UTC)
No, it does not. The expected value does not minimize that average distance. The median does. The expeected values minimizes the average square of the distance. Besides, it's not clear that estimation is what's being done here. Michael Hardy (talk) 19:07, 7 January 2008 (UTC)
Greetings[edit]
Hi Alex. So there you are, hiding under a ?Latinate variant. Psychology articles are in a frightful mess around this neck of the woods. Tony (talk) 06:16, 29 November 2008 (UTC) PS You may recognise the white staircase and my daughter on my talk page. Tony (talk) 06:17, 29 November 2008 (UTC)