Calculating Probability of a Poisson Process w/ Parameter λ

In summary, the conversation is discussing the problem of finding the probability that N((1,2])=3 given N((1,3])>3, using the fact that this is equal to P(A&B)/P(B) where A=N((1,2]) and B=N((1,3])>3. The conversation also mentions an alternative problem with a more insightful answer.
  • #1
chimychang
5
0
I need some help on the following question: Let N() be a poisson process with parameter [tex] \lambda [/tex].

I need to find that probability that

[tex] N((1,2]) = 3 [/tex] given [tex] N((1,3]) > 3 [/tex]

I know that this is equal to the probability that

[tex] P(A \cap B) / P(B) [/tex] where A = N((1,2]) and B = N((1,3]) > 3, but I'm not sure where to go from there.
 
Physics news on Phys.org
  • #2
chimychang said:
[tex] P(A \cap B) / P(B) [/tex] where A = N((1,2]) and B = N((1,3]) > 3, but I'm not sure where to go from there.
Yes, that's the right start. Can you write down the value of P(B)?
For P(A&B), you have "N((1,2])=3 and N((1,3]) > 3". Can you translate that into a combination of the event A and some fact concerning N((2,3])?
 
  • #3
chimychang said:
I need some help on the following question: Let N() be a poisson process with parameter [tex] \lambda [/tex].

I need to find that probability that

[tex] N((1,2]) = 3 [/tex] given [tex] N((1,3]) > 3 [/tex]

I know that this is equal to the probability that

[tex] P(A \cap B) / P(B) [/tex] where A = N((1,2]) and B = N((1,3]) > 3, but I'm not sure where to go from there.

Are you sure you have copied the problem correctly? Getting P{N(1,2]=3|N(1,3]>3} is not too difficult (just use the definition and known expressions), but the answer is not particularly enlightening. However, the alternative problem P{N(1,3]>3|N(1,2]=3} gives a much nicer answer, and one that reveals an important property of Poisson processes.
 

Related to Calculating Probability of a Poisson Process w/ Parameter λ

1. What is a Poisson process?

A Poisson process is a mathematical model used to describe the occurrence of events that happen randomly and independently over time or space. It is named after the French mathematician Siméon Denis Poisson.

2. What is the parameter λ in a Poisson process?

The parameter λ represents the average rate at which events occur in a Poisson process. It is also known as the intensity or rate parameter.

3. How do you calculate the probability of a Poisson process?

The probability of a Poisson process can be calculated using the formula P(k;λ) = (λ^k * e^-λ) / k!, where k is the number of events and λ is the rate parameter. This is also known as the Poisson distribution.

4. Can the probability of a Poisson process be greater than 1?

No, the probability of a Poisson process cannot be greater than 1. This is because the sum of all probabilities in a probability distribution must equal 1.

5. What are some real-life applications of the Poisson process?

The Poisson process has many real-life applications, such as modeling the number of customers arriving at a store, the number of earthquakes in a given area, or the number of phone calls received by a call center. It is also used in traffic flow analysis, inventory management, and queueing theory.

Similar threads

  • Calculus and Beyond Homework Help
Replies
8
Views
800
  • Calculus and Beyond Homework Help
Replies
10
Views
1K
  • Calculus and Beyond Homework Help
Replies
5
Views
434
  • Calculus and Beyond Homework Help
Replies
21
Views
1K
  • Calculus and Beyond Homework Help
Replies
32
Views
2K
  • Calculus and Beyond Homework Help
Replies
2
Views
1K
Replies
2
Views
2K
  • Precalculus Mathematics Homework Help
Replies
2
Views
806
  • Calculus and Beyond Homework Help
Replies
4
Views
1K
Replies
2
Views
1K
Back
Top