Poisson Probability: At Least 50% Defective Brake Lights

In summary: To solve for n, we take the complement of the probability and set it equal to 0.5:P(X \geq 1) = 1 - P(X=0) = 1 - \frac{(0.01n)^0 e^{-0.01n}}{0!} = 1 - e^{-0.01n} = 0.5Solving for n, we get n \approx 69.3. Therefore, a sample size of at least 70 cars is needed to have a 50% probability of containing at least one car with a defective brake light.
  • #1
Amannequin
4
0

Homework Statement



Suppose that 1% of cars have defective brake lights and n cars are to be inspected. How large should n be for the sample to have a probability of at least 50% of containing a car with a defective brake light? Give an answer using a Poisson approximation with an appropriate mean.

The Attempt at a Solution



Let X-Bin(n, 0.01).
We can approximate X with the Poisson distribution assuming n large and with mean 0.01n.
That is, X≈Po(0.01n).
We want P(X=1)≥ 0.5 which yields ne^-0.01n ≥ 50.

Then I'm stuck. Is this correct so far and any direction on where to go from here will be appreciated. Thanks.
 
Physics news on Phys.org
  • #2
Amannequin said:

Homework Statement



Suppose that 1% of cars have defective brake lights and n cars are to be inspected. How large should n be for the sample to have a probability of at least 50% of containing a car with a defective brake light? Give an answer using a Poisson approximation with an appropriate mean.

The Attempt at a Solution



Let X-Bin(n, 0.01).
We can approximate X with the Poisson distribution assuming n large and with mean 0.01n.
That is, X≈Po(0.01n).
We want P(X=1)≥ 0.5 which yields ne^-0.01n ≥ 50.

Then I'm stuck. Is this correct so far and any direction on where to go from here will be appreciated. Thanks.

I think you actually want [itex]P(X \geq 1) \geq 0.5[/itex], since a sample which contains more than one defective car contains a defective car.
 
  • Like
Likes 1 person

1. What is Poisson Probability?

Poisson Probability is a mathematical concept that calculates the likelihood of a certain number of events occurring within a specific time frame, given a known average rate of occurrence.

2. How is Poisson Probability used in relation to defective brake lights?

In the case of defective brake lights, Poisson Probability can be used to determine the likelihood of at least 50% of a certain number of brake lights being defective based on the average rate of defective brake lights.

3. What factors are needed to calculate Poisson Probability for defective brake lights?

The factors needed to calculate Poisson Probability for defective brake lights include the average rate of defective brake lights, the time frame in which the calculation is being made, and the desired probability (in this case, at least 50%).

4. How can Poisson Probability be used to improve brake light quality?

Poisson Probability can be used by manufacturers to identify areas of improvement in their brake light production process. By analyzing the probability of defective brake lights based on certain factors, adjustments can be made to improve quality control and decrease the likelihood of defective brake lights.

5. Is Poisson Probability the only method for predicting defective brake lights?

No, there are other methods for predicting defective brake lights, such as statistical process control and Six Sigma methodologies. However, Poisson Probability is a commonly used and effective method for making these types of predictions.

Similar threads

  • Calculus and Beyond Homework Help
Replies
7
Views
1K
  • Calculus and Beyond Homework Help
Replies
1
Views
1K
Replies
2
Views
3K
  • Calculus and Beyond Homework Help
Replies
1
Views
2K
Replies
1
Views
997
  • Calculus and Beyond Homework Help
Replies
4
Views
1K
Replies
1
Views
1K
  • Calculus and Beyond Homework Help
Replies
2
Views
12K
  • Calculus and Beyond Homework Help
Replies
1
Views
2K
  • Calculus and Beyond Homework Help
Replies
4
Views
2K
Back
Top