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

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SUMMARY

The discussion focuses on calculating the probability P{S < t < S + R} for independent exponentially distributed random variables S and R with rates λ and μ. The user expresses confusion regarding the inequalities involving the variable t and seeks clarification on conditioning methods. A key insight provided is the transformation of the problem to compute P{U < R}, where U is defined as U = t - S. This approach simplifies the calculation by focusing on the relationship between U and R.

PREREQUISITES
  • Understanding of independent random variables
  • Familiarity with exponential distribution and its properties
  • Knowledge of probability conditioning techniques
  • Basic skills in manipulating inequalities involving random variables
NEXT STEPS
  • Study the properties of independent exponential random variables
  • Learn about conditioning in probability theory
  • Explore the concept of transformations in probability distributions
  • Research applications of the cumulative distribution function (CDF) in probability calculations
USEFUL FOR

This discussion is beneficial for statisticians, data scientists, and students studying probability theory, particularly those working with exponential distributions and seeking to understand complex probability calculations.

motherh
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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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motherh said:
. I can compute something like P{S < R}

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

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