Template:LognormalDistribution: Difference between revisions

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::<math>\begin{align}
::<math>\begin{align}
& f(t)=\frac{1}{t{\sigma}_{t'}\sqrt{2\pi}}e^{-\tfrac{1}{2}(\tfrac{t'-{\mu'}}{\sigma_{t'}})^2}\\
& f(t)=\frac{1}{t{\sigma'}\sqrt{2\pi}}e^{-\tfrac{1}{2}(\tfrac{t'-{\mu'}}{\sigma'})^2}\\
& f(t)\ge  0,t>0,{{\sigma }_{t'}}>0 \\
& f(t)\ge  0,t>0,{\sigma'}>0 \\
& {t'}=  \ln (t)  
& {t'}=  \ln (t)  
\end{align}
\end{align}
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::<math>\begin{align}
::<math>\begin{align}
  &  {\mu'}= \text{mean of the natural logarithms of the times-to-failure} \\  
  &  {\mu'}= \text{mean of the natural logarithms of the times-to-failure} \\  
&  {\sigma_{t'}}= \text{standard deviation of the natural logarithms of the times to failure}   
&  {\sigma'}}= \text{standard deviation of the natural logarithms of the times to failure}   
\end{align}</math>
\end{align}</math>



Revision as of 16:30, 6 February 2012

The Lognormal Distribution

The lognormal distribution is commonly used for general reliability analysis, cycles-to-failure in fatigue, material strengths and loading variables in probabilistic design. When the natural logarithms of the times-to-failure are normally distributed, then we say that the data follow the lognormal distribution.
The [math]\displaystyle{ pdf }[/math] of the lognormal distribution is given by:

[math]\displaystyle{ \begin{align} & f(t)=\frac{1}{t{\sigma'}\sqrt{2\pi}}e^{-\tfrac{1}{2}(\tfrac{t'-{\mu'}}{\sigma'})^2}\\ & f(t)\ge 0,t\gt 0,{\sigma'}\gt 0 \\ & {t'}= \ln (t) \end{align} }[/math]


where,

[math]\displaystyle{ \begin{align} & {\mu'}= \text{mean of the natural logarithms of the times-to-failure} \\ & {\sigma'}}= \text{standard deviation of the natural logarithms of the times to failure} \end{align} }[/math]

The lognormal distribution and its characteristics are presented in more detail in Chapter 10.