Difference between revisions of "Manuals/calci/EXPONDIST"

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*The mean or expected value of the Exponential Distribution is: <math>E[x]=\frac{1}{ λ}</math>
 
*The mean or expected value of the Exponential Distribution is: <math>E[x]=\frac{1}{ λ}</math>
 
*The variance of the Exponential Distribution is: <math>Var[x]=\frac{1}{\lambda^2}</math>.
 
*The variance of the Exponential Distribution is: <math>Var[x]=\frac{1}{\lambda^2}</math>.
 +
 +
==Examples==
 +
Question : If jobs arrive at an average of 15 seconds, λ = 5 per minute, what is the probability of waiting 30 seconds, i.e 0.5 min?
 +
Here λ=5 and x=0.5
 +
=EXPONDIST(0.5,5,TRUE)=0.917915001
 +
=EXPONDIST(5,3,TRUE)=0.999999694
 +
=EXPONDIST(0.4,2,FALSE)=0.898657928"

Revision as of 00:52, 29 November 2013

EXPONDIST(x,Lambda,cum)


  • is the value of the function
  • is the value of the rate parameter
  • is the logical value like TRUE or FALSE

Description

  • This function gives the exponential distribution. This distribution used to model the time until something happens in the process.
  • This describes the time between events in a Poisson process i.e, a process in which events occur continuously and independently at a constant average rate.
  • For e.g Time between successive vehicles arrivals at a workshop.
  • In EXPONDIST(x, lambda,cu), xis the value of the function, lambda is called rate parameter and cu(cumulative) is the TRUE or FALSE. *This function will give the cumulative distribution function , when cu is TRUE,otherwise it will give the probability density function , when cu is FALSE.
  • Suppose we are not giving the cu value, by default it will consider the cu value is FALSE.
  • This function will give the error result when
1.  or  is non-numeric.
2.  or 

The Probability Density Function of an Exponential Distribution is

or

Failed to parse (syntax error): {\displaystyle f(x;\lambda)= λe^{-\lambda x} .H(x)}
  • where is the rate parameter and H(x) is the Heaviside step function
  • This function is valid only on the interval [0,infinity].

The Cumulative Distribution Function is :

or

  • The mean or expected value of the Exponential Distribution is: Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle E[x]=\frac{1}{ λ}}
  • The variance of the Exponential Distribution is: .

Examples

Question : If jobs arrive at an average of 15 seconds, λ = 5 per minute, what is the probability of waiting 30 seconds, i.e 0.5 min? Here λ=5 and x=0.5 =EXPONDIST(0.5,5,TRUE)=0.917915001 =EXPONDIST(5,3,TRUE)=0.999999694 =EXPONDIST(0.4,2,FALSE)=0.898657928"