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# We will focus on x lets change the notation so that

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Unformatted text preview: he variance ¯ is, and even the what the distribution is. We will focus on x . Let’s change the notation so that we know we’re dealing with a ¯ random variable: X is a random variable, x is a realization of it for a given random ¯ sample. Utku Suleymanoglu (UMich) Sampling Distributions 7 / 21 Sampling Distributions Random Variables and Sampling Distributions The way we will think about the random sampling is as following: The aspect of the population that we are interested in (e.g. incomes or heights of people) is generated by a random variable, X . This random variable has an unknown distribution (maybe Normal, maybe not). This random variable has a mean µ and variance σ 2 . We are interested in producing a guess for µ. Expected value of the random variable, µ, is the population parameter we are interested in. We randomly choose a random sample from the population. Each of the n values we draw is a realization of X . So each number in your sample is comes from this random variable with mean µ and variance σ 2 . Another way to think ab...
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## This note was uploaded on 03/17/2014 for the course ECON 404 taught by Professor Staff during the Spring '08 term at University of Michigan.

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