How Do You Calculate P{S < t < S + R} for Independent Exponential Variables?

In summary, the question is asking for the computation of the probability P{S < t < S + R}, but the presence of variables on either side of the inequalities is causing confusion. The asker has tried conditioning on both S and R and has been able to calculate P{S < R}, but is unsure of how to handle the variable t. The responder suggests computing the probability P{U < R} where U = t - S.
  • #1
motherh
27
0
Hi, I have a quick question.

Let R and S be two independent exponentially distributed random variables with rates λ and μ. How would I compute P{S < t < S + R}?

I am a little bit confused because of the variables on either side of the inequalities. I have tried conditioning on both S and R but I am not sure if I'm doing it right here. I can compute something like P{S < R} but the t is throwing me off!

Any help is appreciated!
 
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  • #2
motherh said:
. I can compute something like P{S < R}

Then can't you compute the probability that U < R where U = t - S ?
 

Related to How Do You Calculate P{S < t < S + R} for Independent Exponential Variables?

1. What is an Exponential Random Variable?

An Exponential Random Variable is a type of continuous random variable used in probability and statistics. It represents the time between events occurring in a Poisson process, where events occur continuously and independently at a constant rate.

2. How is an Exponential Random Variable different from other types of random variables?

An Exponential Random Variable differs from other types of random variables in that it models the time between events occurring, rather than the number of events occurring. It is also a continuous random variable, meaning it can take on any value within a certain range.

3. What is the probability distribution of an Exponential Random Variable?

The probability distribution of an Exponential Random Variable follows an exponential function, with the probability of an event occurring decreasing as the time between events increases. It is described by the parameter lambda (λ), which represents the average number of events occurring per unit of time.

4. How is an Exponential Random Variable used in real-world applications?

An Exponential Random Variable is commonly used in fields such as finance, engineering, and physics to model the time between events. It can be used to predict the waiting time for a customer in a queue, the time between machine failures, or the time between radioactive decay events.

5. What is the relationship between an Exponential Random Variable and the Poisson distribution?

An Exponential Random Variable and the Poisson distribution are closely related, as the Exponential Random Variable models the time between events in a Poisson process. The Poisson distribution describes the number of events occurring within a specified time period, while the Exponential Random Variable describes the time between individual events.

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