Poisson Random Variable probability problem

Ok, thank you anyways!In summary, we have a Poisson Random Variable X with a rate of 1 per hour, following the Poisson arrival process. We find that the probability of no arrivals during a 10 hour interval is 0.00001 and the probability of X > 10 arrivals in 2 hours is also 0.00001. The average interarrival time for X is 1 hour. For an interval of 2 hours, we have A = {10 > X > 6}, B = {5 < X < 9}, and we need to find Pr(6 < X < 11|A, B). We also need to find E(X|A ∩ B), E(Y |
  • #1
probhelp150

Homework Statement


X is a Poisson Random Variable with rate of 1 per hour, following the Poisson arrival process
a. Find the probability of no arrivals during a 10 hour interval
b. Find the probability of X > 10 arrivals in 2 hours
c. Find the average interarrival time.
d. For an interval of 2 hours, let A = {10 > X > 6}, B = {5 < X < 9}, then find Pr(6 < X < 11|A, B)
e. Find E(X|A ∩ B) in the previous problem
f. If Y = exp(2X), then find E(Y |A ∪ B).
g. Find E(Y 2 |A ∪ B)
h. Find Var(Y |A ∪ B)

Homework Equations

The Attempt at a Solution


a.
##\lambda = \frac{1}{1 hour}##
##\frac{1}{1 hour} * \frac{10}{10}=\frac{10}{10 hours}##
##\lambda = 10##
##P = \frac{e^{-10}*10^x}{x!}##

b.
##\lambda = 2##
##P = \frac{e^{-2}*2^x}{x!}##
X>10 = 1 - Sum(P(0...10))
##\sum_{n=0}^{10} \frac{e^{-2}*2^x}{x!}= 0.99999##
1-0.99999=0.00001

c.
Average interarrival time = ##\frac{1}{\lambda}=\frac{1}{2}=30 minutes##

Am I doing this right so far?
 
Physics news on Phys.org
  • #2
"a" and "b" look good. For part "a", you need to let x=0, and compute. ## \\ ## "c" I think is just 1/rate=1 hour. ## \\ ## In parts "a" and "b", ## \lambda=rate \times time ##. (The way you computed ## \lambda ## was a little clumsy, but otherwise correct).
 
  • #3
Charles Link said:
"a" and "b" look good. For part "a", you need to let x=0, and compute. ## \\ ## "c" I think is just 1/rate=1 hour. ## \\ ## In parts "a" and "b", ## \lambda=rate \times time ##. (The way you computed ## \lambda ## was a little clumsy, but otherwise correct).
If part c were referring to part b, would the interarrival time be 30 minutes because ##\lambda=2##?
I'm wondering about #2 because that is a really small number... However, if the average number of arrivals is 1 per hour, the chance 5 arrivals per hour (10 in 2 hours) would be fairly low. Is my method of thinking correct?

Do you have any tips for parts d to h?
 
  • #4
probhelp150 said:
If part c were referring to part b, would the interarrival time be 30 minutes because ##\lambda=2##?
I'm wondering about #2 because that is a really small number... However, if the average number of arrivals is 1 per hour, the chance 5 arrivals per hour (10 in 2 hours) would be fairly low. Is my method of thinking correct?

Do you have any tips for parts d to h?
I believe part c is referring to any arbitrary measurement period. How far apart are the arrivals?
 
  • #5
Charles Link said:
I believe part c is referring to any arbitrary measurement period. How far apart are the arrivals?
1 hour apart. I get it now, thanks.
 
  • Like
Likes Charles Link
  • #6
probhelp150 said:
1 hour apart. I get it now, thanks.
I don't understand the notation for part d. I'm not sure exactly what they are asking. Perhaps someone else might be able to help out on that part...
 
  • #7
Charles Link said:
I don't understand the notation for part d. I'm not sure exactly what they are asking. Perhaps someone else might be able to help out on that part...
Ok, thank you anyways!
 

1. What is a Poisson random variable probability problem?

A Poisson random variable probability problem involves calculating the probability of a certain number of events occurring within a specific time or space interval, given a known average rate of occurrence. It is used to model rare or random events, such as car accidents or customer arrivals, in many fields including biology, economics, and engineering.

2. How is a Poisson random variable different from a normal random variable?

A Poisson random variable is used to model events that occur at a constant rate whereas a normal random variable is used to model continuous data that follows a symmetric bell-shaped distribution. Additionally, the values of a Poisson random variable are discrete, while the values of a normal random variable are continuous.

3. What is the formula for calculating the probability of a Poisson random variable?

The formula for calculating the probability of a Poisson random variable is P(X = k) = (e^-λ * λ^k)/k!, where X is the random variable, k is the number of events, and λ is the average rate of occurrence.

4. How can Poisson random variables be applied in real-life situations?

Poisson random variables can be used to model a variety of real-life situations, such as the number of customers arriving at a store in a given hour, the number of accidents on a highway in a month, or the number of mutations in a DNA sequence. They are also commonly used in quality control and reliability analysis.

5. What are some common misconceptions about Poisson random variables?

One common misconception about Poisson random variables is that they can only be used for rare events. While they are commonly used for rare events, they can also be used for events that occur at a higher rate, as long as the events are independent of one another. Another misconception is that the average rate of occurrence must be an integer. The formula for calculating the probability can handle non-integer values for λ.

Similar threads

  • Engineering and Comp Sci Homework Help
Replies
5
Views
1K
  • Engineering and Comp Sci Homework Help
Replies
1
Views
958
  • Calculus and Beyond Homework Help
Replies
8
Views
675
  • Engineering and Comp Sci Homework Help
Replies
3
Views
2K
  • Calculus and Beyond Homework Help
Replies
10
Views
983
  • Math POTW for Graduate Students
Replies
3
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
6
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
3
Views
1K
  • Calculus and Beyond Homework Help
Replies
5
Views
237
Replies
12
Views
736
Back
Top