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>.
 +
*<math>Accuracy</math> is correct decimal places for the result.
 +
** 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>
 +
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>
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<div id="1SpaceContent" class="zcontent" align="left">
 
 
 
It calculates the cumulative lognormal distribution of x, where ln(x) is distributed with parameters as mean and standard deviation.
 
 
 
</div>
 
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<div id="7SpaceContent" class="zcontent" align="left">
 
 
 
·          When arguments are nonnumeric ,LOGNORMDIST shows error.
 
 
 
·          LOGNORMDIST displays 0, when  n ≤ 0 or sd ≤ 0.
 
  
·          The equation for the lognormal cumulative distribution function is:
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==ZOS==
 +
*The syntax is to calculate cumulative log normal distribution in ZOS is <math>LOGNORMDIST(Number,Mean,StandardDeviation,Accuracy)</math>.
 +
**<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}}
  
</div>
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==Examples==
----
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#=LOGNORMDIST(2,5.4,2.76) = 0.044061652
<div id="12SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="left">
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#=LOGNORMDIST(10,24.05,12.95) = 0.046543186
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#=LOGNORMDIST(50,87.0036,42.9784) = 0.026597569
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#=LOGNORMDIST(-10,5,2) = #N/A (NUMBER GREATER THAN (OR) NOT EQUAL TO 0)
  
LOGNORMDIST
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==Related Videos==
  
</div></div>
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{{#ev:youtube|9rMpraPPQ2A|280|center|Lognormal Distribution}}
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<div id="8SpaceContent" class="zcontent" align="left">
 
  
<font size="3"><font face="Times New Roman">Lets see an example in (Column1 Row 1,Column2Row1, Column3Row1)</font></font>
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==See Also==
 +
*[[Manuals/calci/LN  | LN ]]
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*[[Manuals/calci/LOG10  | LOG10 ]]
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*[[Manuals/calci/EXP  | EXP ]]
  
<font size="3">LOGNORMDIST (n, m,sd)</font>
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==References==
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[http://en.wikipedia.org/wiki/Log-normal_distribution Log-normal distribution]
  
<font size="3">LOGNORMDIST (C1R1, C2R1,C3R1)</font>
 
  
<font size="3">i.e. =LOGNORMDIST (5, 4.5, 2.2) is 0.09472</font>
 
  
</div>
 
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<div id="10SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Syntax </div><div class="ZEditBox"><center></center></div></div>
 
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<div id="4SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Remarks </div></div>
 
----
 
<div id="3SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Examples </div></div>
 
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<div id="11SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Description </div></div>
 
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<div id="2SpaceContent" class="zcontent" align="left"><div>
 
  
{| id="TABLE3" class="SpreadSheet blue"
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*[[Z_API_Functions | List of Main Z Functions]]
|- class="even"
 
| class=" " |
 
| Column1
 
| class="        " | Column2
 
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|- class="odd"
 
| class=" " | Row1
 
| class=" " | 5
 
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| class="sshl_f " | 2.2
 
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|- class="even"
 
| class="  " | Row2
 
| class="sshl_f" | 0.094718
 
| class="sshl_f" | 0
 
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|- class="odd"
 
| Row3
 
| class="sshl_f SelectTD SelectTD" |
 
<div id="2Space_Handle" title="Click and Drag to resize CALCI Column/Row/Cell. It is EZ!"></div><div id="2Space_Copy" title="Click and Drag over to AutoFill other cells."></div>
 
| class="sshl_f" |
 
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|- class="even"
 
| Row4
 
| class="sshl_f" |
 
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| class=" " |
 
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|- class="odd"
 
| class="sshl_f" | Row5
 
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<div align="left"></div>''''''</div></div>
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*[[ Z3 |  Z3 home ]]
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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