Answer: Solve Poisson Distribution Prob | Rare Event?

In summary, the Poisson Distribution is used to calculate the probability of a certain number of events occurring in a given time period, based on historical data. In this case, we used it to calculate the probability of a certain number of people entering the ICU on any given day, and on two consecutive days. The probability of less than 2 people entering the ICU on a single day is about 1 in 25, making it a rare event. The probability of less than 2 people entering the ICU on two consecutive days is even rarer.
  • #1
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[SOLVED] Poisson Distribution

Homework Statement



Let X be the number of people entering the ICU in a hospital. From Historical data, we know the average number of people entering ICU on any given day is 5

a) What is the probability that the number of people entering the ICU on any given day is less than 2. Do you think this is a rare event?

b) What is the probability of people entering the ICU on any 2 consecutive day is less than 2. Do you think this is a rare event?

Homework Equations



[tex]P(X = K) = \frac{\mu^k e^{-\mu}}{k!}[/tex]

The Attempt at a Solution



a) [tex]P (X < 2) = P(X=0) + P(X=1) = \frac{5^0 e^{-5}}{0!} + \frac{5^{1} e^{-5}}{1!}
= e^{-5} + 5e^{-5} = 6e^{-5} = 0.0404[/tex]

b) Since it's 2 consecutive days =>P (X < 2)*P (X < 2) = P (X < 2)^2 = 0.0404^2 = 0.00163

How would I determine if it's a rare event? Would I just compare it to 5 people entering the ICU for both cases?

Thank You
 
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  • #2
Your work looks fine (although a couple of signs are switched the fractions in part a -- corrected in following work).
a) The probability is only about .04, so about 1 chance in 25. I'd say that's a fairly rare occurrence.
b) The probability is much less, hence a much rarer event.
 
  • #3
Thank You.
 

1. What is Poisson Distribution?

Poisson Distribution is a probability distribution that is used to model the occurrence of rare events. It calculates the likelihood of a certain number of events happening in a given time period or space, based on the average rate of occurrence and assuming that the events are independent.

2. How is Poisson Distribution different from other probability distributions?

Poisson Distribution is unique in that it only considers the number of occurrences of an event, rather than the magnitude or size of the event. It is also used for rare events, while other distributions such as the normal distribution are used for more common events.

3. What is the formula for solving Poisson Distribution?

The formula for Poisson Distribution is P(x; μ) = (e^-μ * μ^x) / x!, where x is the number of events, μ is the average rate of occurrence, and e is the base of the natural logarithm.

4. How can Poisson Distribution be applied in real life?

Poisson Distribution can be applied in various fields such as finance, biology, and engineering. For example, it can be used to model the number of customers arriving at a store in a given time period, the number of defects in a manufacturing process, or the number of mutations in a DNA sequence.

5. What is considered a rare event in Poisson Distribution?

A rare event in Poisson Distribution is typically defined as an event that has a low probability of occurring, usually less than 5%. This can vary depending on the context and application of the distribution.

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