Poisson distribution question

In summary, the conversation discusses the probability of having exactly 2 months with exactly 4 crimes in a town where crimes occur at a Poisson rate of 2.4 per month. To find the probability, one must use the Poisson distribution to calculate the probability of 4 crimes in 2 months, and then use the binomial distribution to determine the overall probability for the next year. However, the exact method for calculating the probability of 4 crimes in 2 months is unclear.
  • #1
zzod
2
0
Hey guys, I'm kind of stuck on this question.

In a certain town, crimes occur at a Poisson rate of 2.4 per month (i.e. according to a Poisson process with a rate of 2.4 per month). What is the probability of having exactly 2 months (not necessarily consecutive) with exactly 4 crimes during the next year? Assume that every month has the same length.

I know that first you have to find the probability of 4 crimes in 2 months using Poisson distribution then use binomial distribution to answer the question. But I'm not sure how to do the first part! >.<
 
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  • #2
zzod said:
Hey guys, I'm kind of stuck on this question.

In a certain town, crimes occur at a Poisson rate of 2.4 per month (i.e. according to a Poisson process with a rate of 2.4 per month). What is the probability of having exactly 2 months (not necessarily consecutive) with exactly 4 crimes during the next year? Assume that every month has the same length.

I know that first you have to find the probability of 4 crimes in 2 months using Poisson distribution then use binomial distribution to answer the question. But I'm not sure how to do the first part! >.<

If the rate is 2.4 per month, then the probability of a crime happening in any given month = 1 - (1/2.4) (or so I think) = 58.33% approximately. Then the probability of four crimes in two months = the probability of exactly one crime in two months^4.
 
  • #3
Poisson chance of 4 crimes in a month is
[tex]\frac{2.4^4e^{-2.4}}{4!}[/tex]. Use binomial from here.
 
  • #4
CRGreathouse said:
Poisson chance of 4 crimes in a month is
[tex]\frac{2.4^4e^{-2.4}}{4!}[/tex]. Use binomial from here.

I don't think this would work as the question is asking for the probability of exactly 4 crimes occurring in 2 months.
 
  • #5
CRGreathouse said:
Poisson chance of 4 crimes in a month is
[tex]\frac{2.4^4e^{-2.4}}{4!}[/tex]. Use binomial from here.

This is correct. You do mean 4 crimes occurring in each of 2 months right? If not you need to word the question more clearly.
 

What is a Poisson distribution?

A Poisson distribution is a probability distribution that is used to model the number of events that occur in a fixed interval of time or space, given that these events occur independently and at a constant rate. It is often used to analyze rare events and is characterized by a single parameter, lambda, which represents the average number of events that occur in the given interval.

What are the assumptions of a Poisson distribution?

The assumptions of a Poisson distribution include: the events occur independently, the rate at which events occur is constant, the probability of an event occurring in a small interval is proportional to the length of the interval, and the probability of an event occurring in one interval is independent of the probability of an event occurring in another interval.

How do you calculate probabilities using the Poisson distribution?

To calculate probabilities using the Poisson distribution, you need to know the average rate of events (lambda) and the specific number of events you are interested in. Then, you can use the Poisson probability formula, which is P(x) = (e^-lambda * lambda^x)/x!, where x is the number of events and e is the mathematical constant approximately equal to 2.71828.

What is the difference between a Poisson distribution and a normal distribution?

The main difference between a Poisson distribution and a normal distribution is that a Poisson distribution is used to model the number of discrete events that occur in a fixed interval, while a normal distribution is used to model continuous data. Additionally, the shape of a Poisson distribution is skewed to the right, while a normal distribution is symmetric.

In what real-world situations can the Poisson distribution be applied?

The Poisson distribution can be applied in various real-world situations, such as modeling the number of accidents in a given day, the number of customers arriving at a store in an hour, the number of defects in a manufacturing process, and the number of earthquakes in a certain region. It is also commonly used in insurance, finance, and epidemiology to model rare events.

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