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Fundamentals of Probability and Statistics for Engineers

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210 <strong>Fundamentals</strong> <strong>of</strong> <strong>Probability</strong> <strong>and</strong> <strong>Statistics</strong> <strong>for</strong> <strong>Engineers</strong>1.5f Y (y)1.0σ2X = 0.1σ2X = 0.30.5σ2X = 1.00.00 2 4 6 8yFigure 7. 9 Lognormal distribution, f Y (y), with m X ˆ 0, <strong>for</strong> several values <strong>of</strong> 2 Xquantities that are restricted to having only positive values. In addition, f Y (y)takes many different shapes <strong>for</strong> different values <strong>of</strong> m X <strong>and</strong> X ( x > 0). As seenfrom Figure 7.9, the pdf <strong>of</strong> Y is skewed to the right, this characteristic becomingmore pronounced as X increases.It is noted that parameters m X <strong>and</strong> X appearing in the pdf <strong>of</strong> Y are themean <strong>and</strong> st<strong>and</strong>ard deviation <strong>of</strong> X, or ln Y , but not <strong>of</strong> Y . To obtain a morenatural pair <strong>of</strong> parameters <strong>for</strong> f Y (y), we observe that, if medians <strong>of</strong> X <strong>and</strong> Y aredenoted by X <strong>and</strong> Y , respectively, the definition <strong>of</strong> the median <strong>of</strong> a r<strong>and</strong>omvariable gives0:5 ˆ P…Y Y †ˆP…X ln Y †ˆP…X X †;orln Y ˆ X :…7:45†Since, owing to the symmetry <strong>of</strong> the normal distribution,we can write X ˆ m X ;m X ˆ ln Y :…7:46†TLFeBOOK

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