Difference between revisions of "Manuals/calci/poisson"
(Created page with "<div id="6SpaceContent" class="zcontent" align="left"> '''POISSON'''(X, Mean, Cumulative) where, '''X''' - are represents number of events. '''Mean '''- is the e...") |
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− | <div | + | <div style="font-size:30px">'''POISSON(x,m,cu)'''</div><br/> |
+ | *<math>x</math> is the number of events. | ||
+ | *<math>m </math> is the mean | ||
+ | *<math>cu</math> is the logical value like TRUE or FALSE. | ||
− | + | ||
+ | ==Description== | ||
+ | *This function gives the value of the Poisson distribution. | ||
+ | *The Poisson distribution is a discrete probability distribution for the counts of events that occur randomly in a given interval of time. | ||
+ | *It is is used to model the number of events occurring within a given time interval. | ||
+ | *In <math>POISSON(x,m,cu), x </math> is the number of events in a given interval of time, <math> m </math> is the Average numeric value and <math> cu </math> is the logical value. | ||
+ | *If it is TRUE, this function will give the cumulative Poisson probability with the number of random events between 0 and x(included). | ||
+ | *If it is FALSE,this function will give the Poisson probability mass function with the number of events occuring will be exactly x. | ||
+ | *The POSSON probability mass function is: <math> f(x,\lambda)=\frac{\lambda^x.e^{-\lambda}}{x!}, x=0,1,2,...where \lambda is the shape parameter and \lambda>0.e is the base of the natural logarithm (e=2.718282). | ||
+ | *The cumulative Poisson probability function is:F(k,λ)=Summation(k=0 to x) e^-λ .λ^k/k!. | ||
+ | *This function will return the result as error when | ||
+ | 1.x or m is nonnumeric. | ||
+ | 2.x<0 or m<0. | ||
where, | where, | ||
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Lets see an example in (Column1, Row1) | Lets see an example in (Column1, Row1) | ||
− | + | UNIQ1bbe901cd2555324-nowiki-00000004-QINU | |
POISSON returns 0.44568. | POISSON returns 0.44568. | ||
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Cosider an another example | Cosider an another example | ||
− | + | UNIQ1bbe901cd2555324-nowiki-00000005-QINU | |
POISSON returns 0.195367. | POISSON returns 0.195367. |
Revision as of 02:15, 6 January 2014
- is the number of events.
- is the mean
- is the logical value like TRUE or FALSE.
Description
- This function gives the value of the Poisson distribution.
- The Poisson distribution is a discrete probability distribution for the counts of events that occur randomly in a given interval of time.
- It is is used to model the number of events occurring within a given time interval.
- In is the number of events in a given interval of time, is the Average numeric value and is the logical value.
- If it is TRUE, this function will give the cumulative Poisson probability with the number of random events between 0 and x(included).
- If it is FALSE,this function will give the Poisson probability mass function with the number of events occuring will be exactly x.
- The POSSON probability mass function is: <math> f(x,\lambda)=\frac{\lambda^x.e^{-\lambda}}{x!}, x=0,1,2,...where \lambda is the shape parameter and \lambda>0.e is the base of the natural logarithm (e=2.718282).
- The cumulative Poisson probability function is:F(k,λ)=Summation(k=0 to x) e^-λ .λ^k/k!.
- This function will return the result as error when
1.x or m is nonnumeric. 2.x<0 or m<0.
where,
X - are represents number of events.
Mean - is the expected numeric values.
Cumulative - returned the logical value that determines the form of the probability distribution.
If TRUE - returnd the cumulative Poisson probability that the number of random events occuring will be between 0 and X.
If FALSE -returns the Poisson probability mass function that the number of events occuring will be exactly X.
Returns the Poisson distribution.
Formula :-
If Cumulative =FALSE
POISSON = (e-λ λ× ) / x!
If Cumulative = TRUE
POISSON = Σ(e-λ λ× ) /k!
If X orMean is nonnumeric, POISSON returns the #ERROR.
If X < 0 or Mean < 0 ,POISSON returns the #ERROR.
POISSON
Lets see an example in (Column1, Row1)
?UNIQ1bbe901cd2555324-nowiki-00000004-QINU?
POISSON returns 0.44568.
Cosider an another example
?UNIQ1bbe901cd2555324-nowiki-00000005-QINU?
POISSON returns 0.195367.
Column1 | Column2 | Column3 | Column4 | |
Row1 | 0.44568 | |||
Row2 | 0.195367 | |||
Row3 | ||||
Row4 | ||||
Row5 | ||||
Row6 |