Conditional exponential probability

In summary: X)$In summary, the expectation of an exponential distribution with parameter $\lambda$ is $\frac 1 \lambda$.
  • #1
Longines
10
0
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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  • #2
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 ($n=2$)
 
  • #3
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?
 
  • #4
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:
$$E[X|A] = \frac 1 \lambda$$
 
  • #5
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 $p$.
 
  • #6
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

$\chi$ $\sigma$
 

FAQ: Conditional exponential probability

1. What is "conditional exponential probability"?

Conditional exponential probability is a statistical concept used to describe the likelihood of an event occurring given a specific set of conditions or circumstances. It is often used in the context of survival analysis, where it measures the probability of a subject surviving beyond a certain time period given their current status.

2. How is conditional exponential probability calculated?

The formula for calculating conditional exponential probability is P(X > t + h | X > t) = P(X > h), where X is a random variable representing time, t is the current time, and h is the time interval. This formula can be derived from the definition of conditional probability and the properties of exponential distributions.

3. What is the difference between conditional exponential probability and regular exponential probability?

The main difference between conditional exponential probability and regular exponential probability is the inclusion of a specific condition or set of conditions in the calculation. Regular exponential probability only takes into account the overall probability of an event occurring, while conditional exponential probability considers the probability of the event occurring given a specific set of conditions.

4. How is conditional exponential probability used in real life?

Conditional exponential probability is commonly used in survival analysis, which is used to study the time until an event of interest (such as death) occurs. It is also used in various fields of science, such as biology, medicine, and engineering, to model and predict the probability of events occurring under specific conditions.

5. What are some limitations of conditional exponential probability?

One limitation of conditional exponential probability is that it assumes the event of interest is independent of other events. This may not always be the case in real life scenarios, leading to inaccurate predictions. Additionally, it is only applicable to events that follow an exponential distribution, which may not always be the case in real life data.

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