Probability Question - Exponential Distribution

In summary, the conversation discusses finding the probability that a variable X with an exponential distribution and mean μ lies within one standard deviation of its mean. The standard deviation is equal to the mean in this distribution, so the probability is found by calculating P(μ-σ ≤ X ≤ μ+σ). However, it is important to note that μ-σ = 0 and μ+σ = 2μ, so the probability is actually P(0 ≤ X ≤ 2μ).
  • #1
GreenPrint
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Homework Statement



Suppose that X has an exponential distribution with mean μ. Find the probability that x lies within one standard deviation of its mean, that is find P(μ-σ≤X≤μ+σ)

Homework Equations





The Attempt at a Solution



If I'm not mistaken the standard deviation is equal to the mean of an exponential distribution so isn't the answer just zero or am I missing something important here?
 
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  • #2
GreenPrint said:

Homework Statement



Suppose that X has an exponential distribution with mean μ. Find the probability that x lies within one standard deviation of its mean, that is find P(μ-σ≤X≤μ+σ)

Homework Equations





The Attempt at a Solution



If I'm not mistaken the standard deviation is equal to the mean of an exponential distribution so isn't the answer just zero or am I missing something important here?

Yes. You are missing the facts that μ-σ = 0 and μ+σ = 2μ, so you want P(0 ≤ X ≤ 2μ). Why would you suppose that is 0?
 
  • #3
oh thanks i missed that
 

FAQ: Probability Question - Exponential Distribution

What is the Exponential Distribution?

The Exponential Distribution is a probability distribution that models the time between events in a process that occurs continuously and independently at a constant average rate.

What is the formula for the Exponential Distribution?

The probability density function (PDF) for the Exponential Distribution is given by f(x) = λe-λx, where λ is the rate parameter and x is the time between events.

What is the relationship between the Exponential Distribution and the Poisson Distribution?

The Exponential Distribution is closely related to the Poisson Distribution, as it represents the time between events in a Poisson process. In fact, the Exponential Distribution is the continuous version of the discrete Poisson Distribution.

What are the main properties of the Exponential Distribution?

The Exponential Distribution has two main properties: memorylessness and the lack of a maximum value. Memorylessness means that the probability of an event occurring in the next time interval is not affected by how much time has already elapsed. The lack of a maximum value means that the distribution continues infinitely to the right.

How is the Exponential Distribution used in real life?

The Exponential Distribution is commonly used to model the time between customer arrivals, the time between equipment failures, and the time between natural disasters. It is also used in queuing theory and reliability analysis.

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