Difference between revisions of "Manuals/calci/LOGNORMDIST"

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*And φ is the cumulative distribution function of the standard normal distribution.  
 
*And φ 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.
+
*1. Any one of the argument is nonnumeric.
2.suppose <math> x \le 0 </math> or <math> sd \le 0</math>
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*2.suppose <math> x \le 0 </math> or <math> sd \le 0</math>
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It calculates the cumulative lognormal distribution of x, where ln(x) is distributed with parameters as mean and standard deviation.
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==Examples==
 +
#LOGNORMDIST(2,5.4,2.76)=0.044061652
 +
#LOGNORMDIST(10,24.05,12.95)=0.046543186
 +
#LOGNORMDIST(50,87.0036,42.9784)=0.026597569
 +
#LOGNORMDIST(-10,5,2)=NAN
  
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==See Also==
----
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*[[Manuals/calci/LN  | LN ]]
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*[[Manuals/calci/LOG10  | LOG10 ]]
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*[[Manuals/calci/EXP  | EXP ]]
  
·          When arguments are nonnumeric ,LOGNORMDIST shows error.
 
  
·          LOGNORMDIST displays 0, when  n ≤ 0 or sd ≤ 0.
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*[[Manuals/calci/SKEW  | SKEW ]]
 
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*[[Manuals/calci/STDEV | STDEV ]]
·          The equation for the lognormal cumulative distribution function is:
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*[[Manuals/calci/STDEVP | STDEVP ]]
 
 
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LOGNORMDIST
 
 
 
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<font size="3"><font face="Times New Roman">Lets see an example in (Column1 Row 1,Column2Row1, Column3Row1)</font></font>
 
 
 
<font size="3">LOGNORMDIST (n, m,sd)</font>
 
 
 
<font size="3">LOGNORMDIST (C1R1, C2R1,C3R1)</font>
 
 
 
<font size="3">i.e. =LOGNORMDIST (5, 4.5, 2.2) is 0.09472</font>
 
 
 
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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>
 
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<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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{| id="TABLE3" class="SpreadSheet blue"
 
|- class="even"
 
| class=" " |
 
| Column1
 
| class="        " | Column2
 
| class="    " | Column3
 
| class="  " |
 
| class="  " | Column4
 
|
 
|- class="odd"
 
| class=" " | Row1
 
| class=" " | 5
 
| class=" " | 4.5
 
| class="sshl_f " | 2.2
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|
 
|- class="even"
 
| class=" " | Row2
 
| class="sshl_f" | 0.094718
 
| class="sshl_f" | 0
 
| class="sshl_f" |
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|
 
|- 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" |
 
| class="sshl_f" |
 
| class="  " |
 
| class="sshl_f" |
 
|
 
|- class="even"
 
| Row4
 
| class="sshl_f" |
 
| class="sshl_f" |
 
|
 
| class=" " |
 
| class="sshl_f" |
 
|
 
|- class="odd"
 
| class="sshl_f" | Row5
 
| class="sshl_f" |
 
| class=" " |
 
|
 
|
 
| class="  " |
 
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|- class="even"
 
| class=" " | Row6
 
| class="sshl_f" |
 
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Revision as of 01:19, 19 December 2013

LOGNORMDIST((x,m,sd)


  • is the value , is the mean of ,
  • And is the standard deviation of .

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= Failed to parse (syntax error): {\displaystyle μ} , standard deviation = Failed to parse (syntax error): {\displaystyle σ}
  • Then the lognormal cumulative distribution is calculated by:Failed to parse (syntax error): {\displaystyle F(x,μ,σ)=1/2[1+(erf(ln(x)-μ)/σsqrt(2)= φ[(ln(x)-μ)/σ]} 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)
  • And φ 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 nonnumeric.
  • 2.suppose or

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)=NAN

See Also