Difference between revisions of "Manuals/calci/EXPONDIST"
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*Suppose we are not giving the <math>cu</math> value, by default it will consider the <math>cu</math> value is FALSE. | *Suppose we are not giving the <math>cu</math> value, by default it will consider the <math>cu</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> | + | 1. <math>x</math> or <math>lambda</math> is non-numeric. |
2. <math>x<0</math> or <math>lambda \le 0</math> | 2. <math>x<0</math> or <math>lambda \le 0</math> | ||
The Probability Density Function of an Exponential Distribution is | The Probability Density Function of an Exponential Distribution is |
Revision as of 03:00, 5 December 2013
EXPONDIST(x,lambda,cu)
- 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.
- In , is the value of the function, is called rate parameter and (cumulative) is the 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
- The mean or expected value of the Exponential Distribution is:
- The variance of the Exponential Distribution is: .
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"