Solving Poisson Process Problem: Probability of Mis-Diagnosis

  • Thread starter ankitj
  • Start date
  • Tags
    Stuck
In summary, the conversation discusses a problem involving an electronic switching device and its error rate. The problem asks for the probability that a satisfactory device will be misdiagnosed as unsatisfactory based on a 5-hour test period. The solution involves using the Poisson Distribution to calculate the probability of the device having more than 1 error in the 5-hour period. The conversation also includes a clarification on the wording of the question and further guidance on how to solve the problem.
  • #1
ankitj
6
0
Hi everyone,

I am stuck on the problem below. I think it has something to do with Poisson Process??
I would really appreciate it if someone could point me in the right direction.

An electronic switching device occasionally malfunctions and may need to be replaced. It is known that the device is satisfactory if it makes, on average no more than .2 errors per hour. A particular five hour period is chosen as a “test” on the device. If no more than 1 error occurs, the device is considered satisfactory. What is the probability that a satisfactory device will be mis- diagnosed as “unsatisfactory” on the basis of the test?

Thanks
AJ
 
Physics news on Phys.org
  • #2
This has to do with the Poisson Distribution. First you need to figure the mean and the variance of the distribution for the 5-hour period, then calculate the "tail" probability beyond 1.
 
  • #3
Is this correct?

λ = 5*0.2 = 1
P(x>1) = 1-P(x<=1) = 1-(P(x=0) + P(x=1)) = 0.2642

Thanks
AJ
 
  • #4
The question seems strangely worded. The problem indicates that the machine has an expected error rate of 0.2/hr. Then it asks for the probability that it will be "misdiagnosed" as unsatisfactory. The probability it is misdiagnosed may have nothing to do with whether the machine malfuctions. Bad choice of words in my opinion. I suspect what the question is getting at is if X is a random variable that counts the number of errors in the 5-hour window, then what is the probability that X is more than 1.

This is a Poisson distributed random variable (as has been mentioned). The probability distribution function for a Poisson variable with expected rate per unit interval [itex]\lambda[/itex] is:

[tex]P(X=n)=\frac{(\lambda t)^n e^{-\lambda t}}{n!}\text{ for }n=0,1,2,3,\dots[/tex]

where t is the length of the interval over which X is measured.

Here you have [itex]\lambda=0.2\text{ and }t=5[/itex] and you're looking for

[tex]P(X>1)=1-P(x\leq1)=1-P(X=0)-P(X=1)[/tex].

You should be able to navigate from here.

--Elucidus
 
  • #5
Thank you very much for your help. Seems like i was on the right track.
 

1. What is a Poisson process?

A Poisson process is a mathematical model used to describe the occurrence of events over a certain period of time, where the events are independent of each other and the rate of occurrence is constant.

2. How is a Poisson process used in the context of mis-diagnosis probability?

In the context of mis-diagnosis probability, a Poisson process can be used to model the rate at which mis-diagnoses occur. This can help calculate the probability of a mis-diagnosis happening within a given time frame.

3. What information is needed to solve a Poisson process problem related to mis-diagnosis probability?

To solve a Poisson process problem related to mis-diagnosis probability, you will need to know the rate of mis-diagnosis, the time frame in which it is occurring, and the number of mis-diagnoses that have already occurred.

4. Can the Poisson distribution be used to solve a Poisson process problem?

Yes, the Poisson distribution is often used to solve Poisson process problems as it allows for the calculation of probabilities for a certain number of events occurring within a given time frame.

5. How can solving a Poisson process problem help in understanding the probability of mis-diagnosis?

By solving a Poisson process problem, we can calculate the probability of a certain number of mis-diagnoses occurring within a given time frame. This can help us understand the likelihood of a mis-diagnosis happening and inform decision-making in healthcare settings.

Similar threads

  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
7
Views
1K
  • Precalculus Mathematics Homework Help
Replies
19
Views
12K
  • Introductory Physics Homework Help
Replies
6
Views
1K
Replies
2
Views
1K
  • Programming and Computer Science
Replies
1
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
3K
  • Quantum Interpretations and Foundations
Replies
14
Views
2K
  • Calculus and Beyond Homework Help
Replies
7
Views
1K
Back
Top