Difference between revisions of "Manuals/calci/EXPONDIST"
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− | <div style="font-size:30px">'''EXPONDIST(x,lambda, | + | <div style="font-size:30px">'''EXPONDIST(x,lambda,cu)'''</div><br/> |
*<math>x</math> is the value of the function | *<math>x</math> is the value of the function | ||
*<math>lambda(\lambda)</math> is the value of the rate parameter | *<math>lambda(\lambda)</math> is the value of the rate parameter |
Revision as of 03:19, 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 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 (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 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 (syntax error): {\displaystyle E[x]=\frac{1}{ λ}}
- 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"