Difference between revisions of "Manuals/calci/EXPONDIST"

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*Exponential distribution is the only continuous memoryless random distribution. It is a continuous analog of the Geometric distribution.
 
*Exponential distribution is the only continuous memoryless random distribution. It is a continuous analog of the Geometric distribution.
 
*In <math>EXPONDIST(X,Lambda,Cumulative)</math>, <math>X</math> is the value of the function, <math> Lambda</math> is called rate parameter and <math>Cumulative</math> is either TRUE or FALSE.
 
*In <math>EXPONDIST(X,Lambda,Cumulative)</math>, <math>X</math> is the value of the function, <math> Lambda</math> is called rate parameter and <math>Cumulative</math> is either TRUE or FALSE.
*This function will give the Cumulative Distribution Function when <math>cumulative</math> is TRUE, otherwise it will give the Probability Density Function , when <math>cumulative</math> is FALSE.  
+
*This function will give the Cumulative Distribution Function when <math>Cumulative</math> is TRUE, otherwise it will give the Probability Density Function , when <math>Cumulative</math> is FALSE.  
*Suppose we are not giving the <math>cumulative</math> value, by default it will consider the <math>cumulative</math> value is FALSE.  
+
*Suppose we are not giving the <math>Cumulative</math> value, by default it will consider the <math>Cumulative</math> value is FALSE.  
 
*This function will give the error result when
 
*This function will give the error result when
 
  1. <math>X</math> or <math>Lambda</math> is non-numeric.
 
  1. <math>X</math> or <math>Lambda</math> is non-numeric.

Revision as of 16:02, 6 June 2018

EXPONDIST(X,Lambda,Cumulative)


  • 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 is 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.
  • Exponential distribution is the only continuous memoryless random distribution. It is a continuous analog of the Geometric distribution.
  • In , is the value of the function, is called rate parameter and is either TRUE or FALSE.
  • This function will give the Cumulative Distribution Function when is TRUE, otherwise it will give the Probability Density Function , when is FALSE.
  • Suppose we are not giving the value, by default it will consider the 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

  • where is the rate parameter and is the Heaviside step function
  • This function is valid only on the interval [0,infinity].

The Cumulative Distribution Function is : or

ZOS

  • The syntax is to calculate EXPONDIST in ZOS is .
    • where is the value of the function
    • is the value of the rate parameter
    • is the logical value like TRUE or FALSE.
  • For e.g.,EXPONDIST(11..12,2.3..3.3..0.4,FALSE)
Exponential Distribution

Examples

Question : If jobs arrive at an average of 15 seconds, per minute, what is the probability of waiting 30 seconds, i.e 0.5 min? Here and

  • =EXPONDIST(0.5,5,TRUE) = 0.917915001
  • =EXPONDIST(5,3,TRUE) = 0.999999694
  • =EXPONDIST(0.4,2,FALSE) = 0.898657928

Related Videos

Exponential Probability

See Also

References