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some important sampling distribution.docx

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Department
Statistics
Course
STATS 2B03
Professor
Aaron Childs
Semester
Fall

Description
nd October 2 , 2012 Stats 2B03: Statistical Methods for Science Some Important Sampling Distribution 5.3 Central Limit Theorem - Histogram (normal variance) of a population that is normal with mean μ and variance σ 2 - Histogram of population that is not normally distributed, with mean μ and variance σ , sample of size n from this population: X 1avg, 2avg, 3avg Xkavg - what will the histogram of X avgs look like? - Most samples will have an average close to 40 - Symmetric distribution, but is not as spread out - Histogram of X avgwill be approximately normally distributed with mean μ Xavg μ and σ Xavg= √ X avgis approximately normal with μ Xavgμ and σ Xavg √ - if the shape of the original distribution is not normal (or unknown) then the approx
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