Gamma and exponential distribution

In summary, gamma distribution is a continuous probability distribution used to model total time for a certain number of events, while exponential distribution models time between events. Gamma distribution is a generalization of chi-squared distribution and has a mean and variance based on its shape and rate parameters. Exponential distribution is commonly used in reliability analysis to model failure rates and has applications in queuing theory, telecommunication, and population studies.
  • #1
mcguiry03
8
0

Homework Statement


prove that,
for gamma distribution
μ=αθ
σ^2=αθ^2
for exponential distribution
μ=θ
σ^2=θ^2
 
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  • #2
mcguiry03 said:

Homework Statement


prove that,
for gamma distribution
μ=αθ
σ^2=αθ^2
for exponential distribution
μ=θ
σ^2=θ^2

What have you done so far? Show your work.

RGV
 
  • #3
i keep on searching the internet about this type of distribution and i am not an english speaking person that is why i hardly understand what they say... i just wanted to answer this bcos it is a challenge problem for an extra points... the problem is, we skip this topic bcos we can not finish the whole syllabus by the end of our summer classes...
 

FAQ: Gamma and exponential distribution

What is the difference between gamma and exponential distribution?

Gamma distribution is a continuous probability distribution that is used to model the time required for multiple events to occur. Exponential distribution, on the other hand, is used to model the time between events in a Poisson process. In other words, gamma distribution is used to model the total time for a certain number of events, while exponential distribution models the time between each event.

How is gamma distribution related to chi-squared distribution?

Gamma distribution is a generalization of chi-squared distribution. In fact, when the shape parameter of a gamma distribution is an integer, it is equivalent to a chi-squared distribution with the same shape parameter.

What is the mean and variance of gamma distribution?

The mean of a gamma distribution is equal to the shape parameter divided by the rate parameter. The variance is equal to the shape parameter divided by the square of the rate parameter.

How is exponential distribution used in reliability analysis?

Exponential distribution is commonly used in reliability analysis to model the failure rate of a system. It is used to calculate the probability of failure within a certain time period, given the failure rate of the system.

What are the applications of gamma and exponential distribution?

Gamma distribution has various applications in fields such as finance, economics, and engineering, where it is used to model waiting times or durations. Exponential distribution is commonly used in reliability analysis, but it also has applications in areas such as queuing theory, telecommunication, and population studies.

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