How Do Poisson and Binomial Distributions Apply to Wire Flaw Analysis?

We use the binomial distribution to calculate the probability for 3 or less sections to have one flaw or more out of 10 sections. The result should be 0.835.In summary, we are assuming that the number of structural flaws on a long wire follows a Poisson distribution with an average of 1 flaw every 5 meters. For a 20 m long section, the probability of having maximum 2 flaws is 0.238. For a wire sliced into 1 m sections, the probability of having 3 or less sections with at least one flaw out of 10 sections is 0.835.
  • #1
skrat
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Homework Statement


We assume that the number of structural flaws on a long wire have obey Poisson distribution law. On average we find 1 flaw every 5 meters.

a) What is the probability that a 20 m long section will have maximum 2 flaws?
b) We slice the wire into 1 m long sections. What is the probability that 3 or less sections (out of 10) have one flaw or more?

Homework Equations

The Attempt at a Solution



a) $$P=e^{-0.2\cdot 20}(1+0.2\cdot 20+\frac{(0.2\cdot 20)^2}{2})=0.238$$
b) Probability that there is NO mistake on a 1m long section is $$P=1-e^{-0.2}=0.18$$ now using Binomial distribution the probability should be $$P=1-\sum _{i=0}\binom{10}{i}(1-0.18)^i0.18^{10-i}$$ yet the results I have say that $$P=1-\sum _{i=0}\binom{10}{i}0.18^{i}(1-0.18)^{10-i}.$$

I personally disagree with that "official" result but would like to hear your opinion...!
 
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  • #2
Ah, forget it.

b) The probability 0.18 applies to that there is at least one (or more) flaw on a 1 m section.
 

Related to How Do Poisson and Binomial Distributions Apply to Wire Flaw Analysis?

What is the Poisson distribution problem?

The Poisson distribution problem is a type of probability problem that deals with the number of occurrences of an event within a specific time or space interval. It is used to model rare events, such as the number of customers entering a store in a given hour or the number of accidents on a particular stretch of road.

What is the formula for the Poisson distribution?

The formula for the Poisson distribution is P(x) = (e^-λ * λ^x) / x!, where λ is the average number of occurrences of the event and x is the number of occurrences we are interested in.

What are the assumptions of the Poisson distribution?

The assumptions of the Poisson distribution include: (1) the events occur independently of each other, (2) the average rate of occurrence remains constant over time or space, and (3) the probability of an event occurring is proportional to the size of the time or space interval.

When is the Poisson distribution used?

The Poisson distribution is used when we are interested in the number of occurrences of a rare event within a specific time or space interval. It is commonly used in fields such as insurance, finance, and manufacturing to predict the likelihood of rare events.

How do you solve a Poisson distribution problem?

To solve a Poisson distribution problem, you first need to identify the average rate of occurrence (λ) and the number of occurrences you are interested in (x). Then, plug these values into the Poisson distribution formula (P(x) = (e^-λ * λ^x) / x!) to calculate the probability of getting x number of occurrences. You can also use a calculator or statistical software to solve the problem.

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