Conditional exponential probability

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SUMMARY

The discussion centers on calculating the expected value of a random variable X, which follows an exponential distribution with parameters λ and μ, conditional on event A and its complement A^c, respectively. The law of total expectation is applied, leading to the formula E[X] = E[X|A] * P(A) + E[X|A^c] * P(A^c). The final expression for E[X] is derived as E[X] = (p/λ) + ((1 - p)/μ), where p represents the probability of event A.

PREREQUISITES
  • Understanding of exponential distributions and their parameters (λ and μ).
  • Familiarity with the law of total expectation in probability theory.
  • Basic knowledge of conditional probability and events.
  • Ability to manipulate mathematical expressions involving probabilities and expectations.
NEXT STEPS
  • Study the properties of exponential distributions, focusing on their expected values.
  • Learn more about the law of total expectation and its applications in probability.
  • Explore conditional probability and its implications in statistical modeling.
  • Investigate advanced topics in probability theory, such as mixtures of distributions.
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Students and professionals in statistics, data science, and actuarial science who are working with probabilistic models and need to understand conditional expectations in exponential distributions.

Longines
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Hello all,

I've been stuck on this question for a while and it's annoying the stew out of me!

I know it's a basic definition type of question, but I can't seem to understand it. Can any of you help?

Question:
Let X be a random variable and A be an event such that, conditional on A, X is exponential with parameter λ, and conditional on $A^c$ (A complement), X is exponential with parameter μ.
Write E[X] in terms of λ, μ and p, the probability of A
 
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Hello

Thankyou for sharing your problem with us at the MHB! :)

I suggest, you make a first step by writing down the law of total expectation:

$E[X] = \sum_{i=1}^{n} E[X|A_i]\cdot P(A_i)$

In this specific case the sum has only two terms ($n=2$)
 
lfdahl said:
Hello

Thankyou for sharing your problem with us at the MHB! :)

I suggest, you make a first step by writing down the law of total expectation:

$E[X] = \sum_{i=1}^{n} E[X|A_i]\cdot P(A_i)$

In this specific case the sum has only two terms ($n=2$)
I figured it had something to do with this, but I don't understand how I express it with lambda and such.

Could you please elaborate?
 
Longines said:
I figured it had something to do with this, but I don't understand how I express it with lambda and such.

Could you please elaborate?

The expectation of an exponential distribution with parameter $\lambda$ is $\frac 1 \lambda$.
So:
$$E[X|A] = \frac 1 \lambda$$
 
Longines said:
I figured it had something to do with this, but I don't understand how I express it with lambda and such.

Could you please elaborate?

First step:$E[X] = E[X|A] \cdot P(A)+E[X|A^c] \cdot P(A^c)$According to #4 you know $E[X|A]$ and $E[X|A^c]$ as $\frac{1}{\lambda}$ and $\frac{1}{\mu}$ respectively.If $P(A)=p$ then what is $P(A^c)$?

Now, try to express $E[X]$ in terms of $\lambda$, $\mu$ and $p$.
 
Longines said:
Hello all,

I've been stuck on this question for a while and it's annoying the hell out of me!

I know it's a basic definition type of question, but I can't seem to understand it. Can any of you help?

Question:
Let X be a random variable and A be an event such that, conditional on A, X is exponential with parameter λ, and conditional on $A^c$ (A complement), X is exponential with parameter μ.
Write E[X] in terms of λ, μ and p, the probability of A

If $P \{A\} = p$ and $P \{A^{c}\} = 1 - p$, then is...

$\displaystyle E \{X\} = \frac{p}{\lambda} + \frac{1 - p}{\mu}\ (1)$

Kind regards

$\chi$ $\sigma$
 

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