STAT 4444 Study Guide - Final Guide: Likelihood Function, Random Variable, Normal Distribution
5 Apr 2020
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Lecture 14: estimation & inference of a population variance. Class business: homework iii due on april 5 at 11:59 p. m. Let y1, y2, , yn be randomly sampled from a normal distribution. The su cient statistic for 2 is s2 = p(yi )2 distribution using this su cient statistic can be written as the following: n. We need a density for a random variable with support on the positive real line in which the ran- dom variable appears in the same functional form as in the last formula. Looking at the distributions table, we can determine the prior distribution. p(y| , ) = 1. 2. 1 selecting , parameters: plot inverse gamma densities with di erent parameter values until you nd one that matches your beliefs, decide on appropriate numeric values for the mean and variance of the prior distribution for. 1. 3 updating the prior to obtain a posterior. Recall: posterior likelihood prior p( 2|y) =
