Poisson Distribution of Accidents

In summary, the conversation discusses the probability of at least 2 days with more than one driving accident in the next 3 years in New York, based on the assumption that all days are alike and the Poisson approximation. The conversation also mentions calculating the probability of 0 and 1 days with more than one accident, and how to estimate the mean daily number of accidents using the given data.
  • #1
bitty
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Homework Statement


In New York in the last 3 years there were 55 driving accidents. Assume all days are alike. What is the approximate probability that "in the next 3 years there will be at least 2 days with more than one accident".


Homework Equations


Poisson approximation


The Attempt at a Solution


P[in the next 3 years there will be at least 2 days with more than one accident]=
1-P[in the next 3 years there will be 0 days with more than one accident]-P[in the next 3 years there will be 1 day with more than one accident]

P[in the next 3 years there will be 0 days with more than one accident] is simple to calculate: 1095!/(1040!*1095^55), w/ 3 years=1095 days.

But I have no idea how to calculate P[in the next 3 years there will be 1 day with more than one accident].
 
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  • #2
bitty said:

Homework Statement


In New York in the last 3 years there were 55 driving accidents. Assume all days are alike. What is the approximate probability that "in the next 3 years there will be at least 2 days with more than one accident".


Homework Equations


Poisson approximation


The Attempt at a Solution


P[in the next 3 years there will be at least 2 days with more than one accident]=
1-P[in the next 3 years there will be 0 days with more than one accident]-P[in the next 3 years there will be 1 day with more than one accident]

P[in the next 3 years there will be 0 days with more than one accident] is simple to calculate: 1095!/(1040!*1095^55), w/ 3 years=1095 days.

But I have no idea how to calculate P[in the next 3 years there will be 1 day with more than one accident].

If you assume that the daily number of accidents is a Poisson random variable with some mean r, what is the expected number of accidents 3 years = 1095 days? Based on the only data available, how would you estimate the value of r?

Now assuming the value of r you obtained above, what is p2 = P{>= 2 accidents in any single day}? Take it from there.

RGV
 

FAQ: Poisson Distribution of Accidents

What is the Poisson Distribution of Accidents?

The Poisson Distribution of Accidents is a statistical model that describes the probability of a certain number of accidents occurring within a specific time period, given a known average rate of accidents.

How is the Poisson Distribution of Accidents calculated?

The Poisson Distribution of Accidents is calculated using the formula P(x;λ) = (e^-λ * λ^x) / x!, where x is the number of accidents, and λ is the average rate of accidents.

What is the difference between Poisson Distribution and Normal Distribution?

The main difference between Poisson Distribution and Normal Distribution is that Poisson Distribution is used to model discrete data, such as the number of accidents, while Normal Distribution is used to model continuous data.

What are the assumptions of the Poisson Distribution of Accidents?

The assumptions of the Poisson Distribution of Accidents include: the number of accidents occurring in a specific time period is independent of the number of accidents occurring in any other time period, accidents occur at a constant rate, and the probability of an accident occurring is the same for all time periods.

How is the Poisson Distribution of Accidents used in real life?

The Poisson Distribution of Accidents is commonly used in risk management, insurance, and safety planning to predict the number of accidents that may occur in a given time period. It is also used in traffic engineering to analyze accident patterns and determine appropriate safety measures.

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