The arrivals of clients at a service firm in Santa Clara is a random variable from Poisson distribution with rate 2 arrivals per hour. What is the probability that in one hour more than 5 clients arrive

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Answer:

1.76% probability that in one hour more than 5 clients arrive

Step-by-step explanation:

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:

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

In which

x is the number of sucesses

e = 2.71828 is the Euler number

[tex]\mu[/tex] is the mean in the given time interval.

The arrivals of clients at a service firm in Santa Clara is a random variable from Poisson distribution with rate 2 arrivals per hour.

This means that [tex]\mu = 2[/tex]

What is the probability that in one hour more than 5 clients arrive

Either 5 or less clients arrive, or more than 5 do. The sum of the probabilities of these events is decimal 1. So

[tex]P(X \leq 5) + P(X > 5) = 1[/tex]

We want P(X > 5). So

[tex]P(X > 5) = 1 - P(X \leq 5)[/tex]

In which

[tex]P(X \leq 5) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) + P(X = 5)[/tex]

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

[tex]P(X = 0) = \frac{e^{-2}*2^{0}}{(0)!} = 0.1353[/tex]

[tex]P(X = 1) = \frac{e^{-2}*2^{1}}{(1)!} = 0.2707[/tex]

[tex]P(X = 2) = \frac{e^{-2}*2^{2}}{(2)!} = 0.2707[/tex]

[tex]P(X = 3) = \frac{e^{-2}*2^{3}}{(3)!} = 0.1804[/tex]

[tex]P(X = 4) = \frac{e^{-2}*2^{4}}{(4)!} = 0.0902[/tex]

[tex]P(X = 5) = \frac{e^{-2}*2^{5}}{(5)!} = 0.0361[/tex]

[tex]P(X \leq 5) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) + P(X = 5) = 0.1353 + 0.2702 + 0.2702 + 0.1804 + 0.0902 + 0.0361 = 0.9824[/tex]

[tex]P(X > 5) = 1 - P(X \leq 5) = 1 - 0.9824 = 0.0176[/tex]

1.76% probability that in one hour more than 5 clients arrive

Answer:

Probability that in one hour more than 5 clients arrive is 0.0166.

Step-by-step explanation:

We are given that the arrivals of clients at a service firm in Santa Clara is a random variable from Poisson distribution with rate 2 arrivals per hour.

The Poisson distribution is foe random variable is given by;

     [tex]P(X=x) = \frac{e^{-\lambda} \times \lambda^{x} }{x!} ; x = 0,1,2,3,....[/tex]

where, [tex]\lambda[/tex] = rate of arrival per hour =2

Let X = Arrival of clients

So, Probability that in one hour more than 5 clients arrive = P(X > 5)

P(X > 5) = [tex]1-P(X \leq 5)[/tex]

P(X [tex]\leq[/tex] 5) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) + P(X = 5)  

              = [tex]\frac{e^{-2} \times 2^{0} }{0!} +\frac{e^{-2} \times 2^{1} }{1!} +\frac{e^{-2} \times 2^{2} }{2!} +\frac{e^{-2} \times 2^{3} }{3!} +\frac{e^{-2} \times 2^{4} }{4!} +\frac{e^{-2} \times 2^{5} }{5!}[/tex]

              = 0.1353 + 0.2707 + 0.2707 + 0.1804 + 0.0902 + 0.0361

              = 0.9834

So, P(X > 5) = [tex]1-P(X \leq 5)[/tex] = 1 - 0.9834 = 0.0166

Therefore, probability that in one hour more than 5 clients arrive is 0.0166.

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