What Is the Probability of Zero Cracks in 5 Miles of Highway?

In summary, the conversation discusses the assumption that the number of significant cracks in a section of interstate highway follows a Poisson distribution with a mean of two cracks per mile. The probability of there being no cracks that require repair in 5 miles of highway is calculated using this assumption, but it may not accurately represent the actual probability due to potential factors such as the uniform distribution of defects and varying conditions.
  • #1
bartowski
9
0
The number of cracks in a section of interstate highway that are significant enough to require repair is assumed
to follow a Poisson distribution with a mean of two cracks per mile. What is the probability that there are no cracks that require repair in 5 miles of highway?

any help guys? :)
 
Physics news on Phys.org
  • #2
bartowski said:
The number of cracks in a section of interstate highway that are significant enough to require repair is assumed
to follow a Poisson distribution with a mean of two cracks per mile. What is the probability that there are no cracks that require repair in 5 miles of highway?

any help guys? :)

Just because the mean is a small number doesn't mean it's a Poisson process. In addition it's hard to make the argument that the observations are independent. The stretch of pavement was probably laid at the same time by the same method. If there are defects, I would expect the probability of defects has a uniform distribution along the length of the road under constant conditions. For inconstant conditions, you can't assume a constant distribution.

As an a academic exercise in irrelevant statistics, you would find the probability of 0 defects in one mile under the Poisson distribution with a mean of 2 and raise that value to the fifth power. It has nothing to do with the specific problem you described.
 
Last edited:

FAQ: What Is the Probability of Zero Cracks in 5 Miles of Highway?

What is a Poisson distribution problem?

A Poisson distribution problem is a statistical problem that 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.

What are the key characteristics of a Poisson distribution?

The key characteristics of a Poisson distribution include:

  • The events occur independently of each other
  • The average rate of occurrence is known and constant
  • The probability of an event occurring is the same for all time or space intervals
  • The events can occur an unlimited number of times

How do you calculate the probability in a Poisson distribution problem?

The probability in a Poisson distribution problem can be calculated using the formula P(x; λ) = (e^-λ * λ^x) / x!, where x is the number of events, and λ is the average rate of occurrence.

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

A Poisson distribution is used to calculate the probability of a discrete number of events occurring within a specific time or space interval, while a normal distribution is used to calculate the probability of a continuous variable falling within a certain range. Additionally, a Poisson distribution is skewed to the right, while a normal distribution is symmetrical.

What are some real-world applications of the Poisson distribution?

The Poisson distribution is commonly used in various fields, including:

  • Insurance - to calculate the probability of future claims
  • Business - to predict the number of customers or sales in a given time period
  • Manufacturing - to estimate the number of defects in a product
  • Telecommunications - to predict the number of calls a switchboard will receive
Back
Top