Manuals/calci/poisson

POISSON(x,m,cu)

• $x$ is the number of events.
• $m$ is the mean
• $cu$ 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 $POISSON(x,m,cu),x$ is the number of events in a given interval of time, $m$ is the Average numeric value and $cu$ 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 occurring will be exactly x.
• The $POISSON$probability mass function is: $f(x,\lambda )={\frac {\lambda ^{x}.e^{-\lambda }}{x!}}$, $x=0,1,2,...where<math>\lambda$ is the shape parameter and $\lambda$>0. $e$ is the base of the natural logarithm (e=2.718282).
• The cumulative Poisson probability function is:$F(k,\lambda )=\sum _{k=0}^{x}{\frac {e^{-\lambda }.\lambda ^{k}}{k!}}$.
• This function will return the result as error when

1.$x$ or $m<math>isnon-numeric.2.<math>x<0$ or $m<0$.

Examples

1. POISSON(6,2,TRUE)=0.995466194
2. POISSON(6,2,FALSE)=0.012029803
3. POISSON(10.2,7,TRUE)=0.901479206
4. POISSON(10.2,7,FALSE)=0.070983269
5. POISSON(6,0,TRUE)=1

See Also

• EXPONDIST

References

Poisson distribution