Difference between revisions of "Manuals/calci/EXPONDIST"
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==Description== | ==Description== | ||
− | *This function gives the Exponential Distribution. This distribution used to model the time until something happens in the process. | + | *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. | *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. | *For e.g Time between successive vehicles arrivals at a workshop. | ||
− | *In EXPONDIST(x, lambda,cu), | + | *In EXPONDIST(x, lambda,cu), <math>x</math> is the value of the function, <math>lambda</math> is called rate parameter and <math>cu</math>(cumulative) is the TRUE or FALSE. |
− | *Suppose we are not giving the cu value, by default it will consider the cu value is FALSE. | + | *This function will give the Cumulative Distribution Function when <math>cu</math> is TRUE, otherwise it will give the Probability Density Function , when <math>cu</math> 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>\lambda</math> is non-numeric. | 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 | + | The Probability Density Function of an Exponential Distribution is |
:<math>f(x,\lambda)=\lambda e^{-\lambda x} , x \ge 0 </math> | :<math>f(x,\lambda)=\lambda e^{-\lambda x} , x \ge 0 </math> | ||
:<math> =0 , x<0</math> | :<math> =0 , x<0</math> | ||
or | or | ||
− | :<math>f(x;\lambda)= | + | :<math>f(x;\lambda)= \lambda e^{-\lambda x} .H(x)</math> |
− | *where <math>\lambda</math> is the rate parameter and H(x) is the Heaviside step function | + | *where <math>\lambda</math> is the rate parameter and <math>H(x)</math> is the Heaviside step function |
*This function is valid only on the interval [0,infinity]. | *This function is valid only on the interval [0,infinity]. | ||
The Cumulative Distribution Function is : | The Cumulative Distribution Function is : | ||
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:<math>F(x,\lambda)=1-e^{-\lambda x}.H(x)</math> | :<math>F(x,\lambda)=1-e^{-\lambda x}.H(x)</math> | ||
− | *The mean or expected value of the Exponential Distribution is: <math>E[x]=\frac{1}{ | + | *The mean or expected value of the Exponential Distribution is: <math>E[x]=\frac{1}{\lambda}</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>. | ||
Revision as of 03:32, 4 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 EXPONDIST(x, lambda,cu), 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 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"