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Cars arriving for gasoline at a Shell station follow a Poisson distribution with a mean of 1010 per hour. (Enter all answers rounded to at least 3 decimal places.) (a) Determine the probability that over the next hour, only one car will arrive. (b) Compute the probability that in the next 3 hours, more than 29 cars will arrive.

User Olavakodan
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1 Answer

3 votes

Answer:

a)
P(X=1) = (e^(-10) 10^1)/(1!)= 0.000454

b) For this case the new parameter
\lambda would be:


\lambda = 10 (cars)/(hour) * 3 hours =30

And we want to calculate the following probability:


P(X >29)

And we can use the complement rule for this case:


P(X >29) =1-P(X\leq 29)

And for this case we can use the following excel code in order to find the required probability:

"=1-POISSON.DIST(29,30,TRUE)"

And we got:
P(X >29) =1-P(X\leq 29)=0.5243

Explanation:

Part a

Let X the random variable that represent the number of cars arriving for gasoline at Shell station. We know that
X \sim Poisson(\lambda= 10)

The probability mass function for the random variable is given by:


f(x)=(e^(-\lambda) \lambda^x)/(x!) , x=0,1,2,3,4,...

And for this case we want this probability:


P(X=1)

Using the probability mass function we got:


P(X=1) = (e^(-10) 10^1)/(1!)= 0.000454

Part b

For this case the new parameter
\lambda would be:


\lambda = 10 (cars)/(hour) * 3 hours =30

And we want to calculate the following probability:


P(X >29)

And we can use the complement rule for this case:


P(X >29) =1-P(X\leq 29)

And for this case we can use the following excel code in order to find the required probability:

"=1-POISSON.DIST(29,30,TRUE)"

And we got:
P(X >29) =1-P(X\leq 29)=0.5243

User Maksim Vorontsov
by
5.1k points
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