Conditional exponential probability

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Discussion Overview

The discussion revolves around calculating the expected value of a random variable X that follows different exponential distributions based on the occurrence of an event A and its complement. Participants explore the application of the law of total expectation in this context, focusing on expressing E[X] in terms of the parameters λ, μ, and the probability p of event A.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Homework-related

Main Points Raised

  • One participant presents a problem involving a random variable X that is exponential with parameters λ and μ depending on the event A and its complement.
  • Another participant suggests using the law of total expectation to express E[X] as a sum of conditional expectations weighted by their probabilities.
  • A later reply confirms that the expectation of an exponential distribution with parameter λ is 1/λ, leading to the expression E[X|A] = 1/λ.
  • Further contributions clarify that E[X] can be expressed as E[X] = E[X|A] * P(A) + E[X|A^c] * P(A^c), with specific values for E[X|A] and E[X|A^c] provided.
  • One participant proposes a formula for E[X] as E[X] = (p/λ) + ((1 - p)/μ), based on the probabilities of A and its complement.

Areas of Agreement / Disagreement

Participants generally agree on the application of the law of total expectation and the expressions for E[X|A] and E[X|A^c]. However, there is no explicit consensus on the final expression for E[X], as it is presented as a proposal rather than an established conclusion.

Contextual Notes

The discussion does not resolve potential assumptions regarding the independence of events or the definitions of the parameters involved. There may also be unresolved steps in deriving the final expression for E[X].

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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