Solve Probability Question Using Poisson Distribution: Get Odds of Overuse

In summary, the probability of an employee taking exactly 9 pairs of earplugs per week is very low (5.92x10^-14) using the Poisson Distribution formula. This means that the odds of an employee taking exactly 9 pairs of earplugs per week is very unlikely.
  • #1
statsluke
5
0
Could anybody attempt to solve this probability question? It incorporates the Poisson Distribution. Thank You.

A company finds that it issues a mean of 7 pairs of earplugs a week to any employee. What is the probability that the number of pairs taken by any employee is 9 per week? (Using the Poisson Distribution). Explain what the odds are of such overuse.
 
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  • #2
Pretty much straightforward question, what have u attempted?

-- AI
 
  • #3
Hello Tenali,

Thanks for your response. I cannot find the formula to answer this problem which makes it incresingly difficult to answer.
 
  • #5
Answer

Poisson Distribution: the probability that n events happened within an interval of length t has a Poisson distribution such that:

P{N(t)=n} = exp(-mt)(mt)^n/n!, for t>=0
where m (often defined as lamda) is the mean rate, i.e., m = 1/mean

For this problem, if we define an event to be a pair of earplug to be issued to an employee, then we are asked to find the probability that exactly 9 pairs of earplugs are taken by any employee a week, thus,
t = 1 week, (note that m and t have the same time units), n = 9
P{N(1)=9}=exp(-1/7*1)(1/7*1)^9/9! = 5.92x10^-14 (apprxo.)
 

FAQ: Solve Probability Question Using Poisson Distribution: Get Odds of Overuse

What is the Poisson distribution and how is it used in probability?

The Poisson distribution is a mathematical probability distribution that is used to model the probability of a certain number of events occurring within a specific time or space interval. It is often used to analyze data that involves counts or frequencies, such as the number of customers in a store or the number of accidents on a road. It is also used to calculate the probability of rare events.

How can the Poisson distribution be applied to the concept of overuse?

The Poisson distribution can be applied to overuse by using it to calculate the probability of a certain number of overuse events occurring within a specific time interval. For example, if you want to know the odds of a machine breaking down due to overuse in a given week, you can use the Poisson distribution to calculate the probability of a certain number of breakdowns happening in that time period.

What information is needed to solve a probability question using the Poisson distribution?

To solve a probability question using the Poisson distribution, you will need to know the average rate or frequency of the event occurring, as well as the specific time or space interval in which the event will be observed. For example, if you want to calculate the odds of a car accident occurring on a specific road in a given day, you would need to know the average number of accidents on that road per day and the length of the observation period.

Can the Poisson distribution be used for events that are not rare?

Yes, the Poisson distribution can be used for events that are not rare, but it is most accurate when the events being observed are rare. If the events are not rare, it is recommended to use a different probability distribution, such as the binomial distribution, which is better suited for events that occur more frequently.

How do you calculate the odds of overuse using the Poisson distribution?

To calculate the odds of overuse using the Poisson distribution, you would first need to determine the average rate of overuse events occurring in a specific time interval. Then, using the Poisson formula, you would plug in the average rate and the number of overuse events you want to calculate the probability for. The resulting number is the probability or odds of that number of overuse events occurring in that time interval.

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