labclt

# labclt - 1 Y=sq rt(x 2 Y does not appear to have a uniform...

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1. Y=sq rt(x) 2. Y does not appear to have a uniform distribution because not all of the values are equally likely. There is also not a Normal distribution-the histogram is skewed to the left. The heights of the histogram bars generally increase as the value of Y increases. This is because the graph of Y=sqrt(x) generally increases as x increases. 3. The mean is therefore also around .663 and the standard deviation is σ/sqrt(n)=.234915/sqrt(200)=.0166. However, this method cannot be used because this is not a normal model. So the actual standard deviation is probably closer to the sample standard deviation. 4.This is very close to the actual mean(2/3 is about .667) and the actual standard deviation (1/sqrt(18)=.2357). II N Exact mean Mean (YBAR ) Exact SD SD (YB AR) Exact variance Vari-ance (YBAR) 1 2/3 .663 1/sq rt(18) .2349 1/18 (.2349) 2 = .055 5 2/3 .668 (1/sqrt(18))/sqrt(5) .106 .0111 .0112 10 2/3 .676 (1/sqrt(18))/sqrt(10) .074 1/10 2 x (10 x 1/18) .0055 40 2/3 .669 (1/sqrt(18))/sqrt(40)

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## This note was uploaded on 11/11/2009 for the course MATH 1710 taught by Professor Staff during the Fall '08 term at Cornell.

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labclt - 1 Y=sq rt(x 2 Y does not appear to have a uniform...

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