Difference between revisions of "Manuals/calci/LOGNORMDIST"

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<div style="font-size:30px">'''LOGNORMDIST((x,m,sd)'''</div><br/>
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<div style="font-size:30px">'''LOGNORMDIST(Number,Mean,StandardDeviation,Accuracy)'''</div><br/>
*<math>x</math> is the value ,<math> m </math> is the mean of <math>log(x)</math>,
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*<math>Number</math> is the value.
*And <math> sd</math> is the standard deviation of <math>log(x)</math>.
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*<math>Mean </math> is the mean value of <math>log(x)</math>,
 +
*<math>StandardDeviation</math> is the standard deviation value of <math>log(x)</math>.
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*<math>Accuracy</math> is correct decimal places for the result.
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** LOGNORMDIST(), returns the cumulative lognormal distribution.
 +
 
 
==Description==
 
==Description==
 
 
*This function gives the value of the cumulative log normal distribution.
 
*This function gives the value of the cumulative log normal distribution.
 
*This  distribution is the continuous probability distribution.  
 
*This  distribution is the continuous probability distribution.  
 
*Lognomal distribution is also called Galton's distribution.
 
*Lognomal distribution is also called Galton's distribution.
 
*A random variable which is log-normally distributed takes only positive real values.
 
*A random variable which is log-normally distributed takes only positive real values.
*Suppose <math>x</math> is normally distributed function ,then <math> y=ln(x)</math> also normally distributed
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*Suppose <math>x</math> is Normally Distributed function, then <math> y=ln(x)</math> also Normally Distributed
* <math> z=exp(y)</math> also normally distributed.  
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*<math> z=exp(y)</math> also Normally Distributed.  
*Let the normal distribution function <math>x </math> and its mean= <math>μ</math>, standard deviation = <math>σ</math>
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*Let the Normal Distribution function <math>x</math> and its Mean= <math>\mu</math>, Standard Deviation = <math>\sigma</math>
*Then the  lognormal cumulative distribution is calculated by:<math> F(x,μ,σ)=1/2[1+(erf(ln(x)-μ)/σsqrt(2)= φ[(ln(x)-μ)/σ]</math> where erf is the  error function( the error function (also called the Gauss error function) is a special function  of sigmoid shape which occurs in probability, statistics and partial differential equations)
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*Then the  lognormal cumulative distribution is calculated by:
*And φ is the cumulative distribution function of the standard normal distribution.  
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<math>F(x,\mu,\sigma)=\frac{1}{2} \left[1+ erf \left (\frac{ln(x)-\mu)}{\sigma \sqrt{2}}\right)\right ]= \varphi\left[\frac{ln(x)-\mu}{\sigma}\right ]</math>
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where <math>erf</math> is the  error function,. The error function (also called the Gauss error function) is a special function  of sigmoid shape which occurs in probability, statistics and partial differential equations.
 +
*And <math>\phi</math> is the Cumulative Distribution function of the Standard Normal distribution.  
 
*This function will give the result as error when
 
*This function will give the result as error when
*1. Any one of the argument is nonnumeric.
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1. Any one of the argument is non-numeric.
*2.suppose <math> x \le 0 </math> or <math> sd \le 0</math>
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2. Suppose <math> Number \le 0 </math> or <math> StandardDeviation \le 0</math>
 +
 
 +
==ZOS==
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*The syntax is to calculate cumulative log normal distribution in ZOS is <math>LOGNORMDIST(Number,Mean,StandardDeviation,Accuracy)</math>.
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**<math>Number</math> is the value.
 +
**<math>Mean </math> is the mean value of <math>log(x)</math>.
 +
**<math> StandardDeviation</math> is the standard deviation value of <math>log(x)</math>.
 +
*For e.g.,LOGNORMDIST(10,8.002,4.501)
 +
{{#ev:youtube|rFnzI4pLSuo|280|center|Log Normal Distribution}}
  
 
==Examples==
 
==Examples==
#LOGNORMDIST(2,5.4,2.76)=0.044061652
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#=LOGNORMDIST(2,5.4,2.76) = 0.044061652
#LOGNORMDIST(10,24.05,12.95)=0.046543186
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#=LOGNORMDIST(10,24.05,12.95) = 0.046543186
#LOGNORMDIST(50,87.0036,42.9784)=0.026597569
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#=LOGNORMDIST(50,87.0036,42.9784) = 0.026597569
#LOGNORMDIST(-10,5,2)=NAN
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#=LOGNORMDIST(-10,5,2) = #N/A (NUMBER GREATER THAN (OR) NOT EQUAL TO 0)
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 +
==Related Videos==
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{{#ev:youtube|9rMpraPPQ2A|280|center|Lognormal Distribution}}
  
 
==See Also==
 
==See Also==
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*[[Manuals/calci/EXP  | EXP ]]
 
*[[Manuals/calci/EXP  | EXP ]]
  
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==References==
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[http://en.wikipedia.org/wiki/Log-normal_distribution Log-normal distribution]
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 +
 +
 +
 +
*[[Z_API_Functions | List of Main Z Functions]]
  
*[[Manuals/calci/SKEW  | SKEW ]]
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*[[ Z3 |   Z3 home ]]
*[[Manuals/calci/STDEV  | STDEV ]]
 
*[[Manuals/calci/STDEVP  | STDEVP ]]
 

Latest revision as of 09:22, 2 June 2020

LOGNORMDIST(Number,Mean,StandardDeviation,Accuracy)


  • is the value.
  • is the mean value of ,
  • is the standard deviation value of .
  • is correct decimal places for the result.
    • LOGNORMDIST(), returns the cumulative lognormal distribution.

Description

  • This function gives the value of the cumulative log normal distribution.
  • This distribution is the continuous probability distribution.
  • Lognomal distribution is also called Galton's distribution.
  • A random variable which is log-normally distributed takes only positive real values.
  • Suppose is Normally Distributed function, then also Normally Distributed
  • also Normally Distributed.
  • Let the Normal Distribution function and its Mean= , Standard Deviation =
  • Then the lognormal cumulative distribution is calculated by:

where is the error function,. The error function (also called the Gauss error function) is a special function of sigmoid shape which occurs in probability, statistics and partial differential equations.

  • And is the Cumulative Distribution function of the Standard Normal distribution.
  • This function will give the result as error when
1. Any one of the argument is non-numeric.
2. Suppose  or 

ZOS

  • The syntax is to calculate cumulative log normal distribution in ZOS is .
    • is the value.
    • is the mean value of .
    • is the standard deviation value of .
  • For e.g.,LOGNORMDIST(10,8.002,4.501)
Log Normal Distribution

Examples

  1. =LOGNORMDIST(2,5.4,2.76) = 0.044061652
  2. =LOGNORMDIST(10,24.05,12.95) = 0.046543186
  3. =LOGNORMDIST(50,87.0036,42.9784) = 0.026597569
  4. =LOGNORMDIST(-10,5,2) = #N/A (NUMBER GREATER THAN (OR) NOT EQUAL TO 0)

Related Videos

Lognormal Distribution

See Also

References

Log-normal distribution