MHB Probability : minutes that customers get served

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SUMMARY

The discussion focuses on calculating the probabilities related to customer service times at a department store, where the average service rate is 30 customers per hour. The service time follows an exponential distribution due to the underlying Poisson process. The calculations for the probabilities are established as follows: for part (a), the probability of being served in less than 15 minutes is given by \( P(X<15) = 1 - e^{-2 \cdot 15} \), and for part (b), the probability of being served between 6 and 8 minutes is calculated as \( P(6 \leq X \leq 8) = (1 - e^{-2 \cdot 8}) - (1 - e^{-2 \cdot 6}) \).

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mathmari
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Hey! :giggle:

The average time of customer service at the cash registers of a department store is $30$ people per hour. If a new customer arrives at the checkout, then calculate the probabilities:

a) to be served in less than 15 minutes

b) to need to be served from 6 to 8 minutes
a) Do we have Poisson disrtibution with $\lambda=30$ ?
But then we consider "minutes" instead of "number of customers".
Could you give me a hint ?

:unsure:
 
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a) 30 people per hour is 2 minutes per person. The wait time is exponentially distributed with this mean. Evaluate the probability that the wait time is less than 15 min given this distribution.

b) I'm not sure what the word "need" means here. If they mean find the probability the customer is served in 6-8 minutes it's just the CDF of the above mentioned distribution evaluated at 8 minutes same evaluated at 6 minutes.
 
romsek said:
a) 30 people per hour is 2 minutes per person. The wait time is exponentially distributed with this mean. Evaluate the probability that the wait time is less than 15 min given this distribution.

b) I'm not sure what the word "need" means here. If they mean find the probability the customer is served in 6-8 minutes it's just the CDF of the above mentioned distribution evaluated at 8 minutes same evaluated at 6 minutes.

How do we know that we have an exponential distribution? :unsure:
 
mathmari said:
How do we know that we have an exponential distribution? :unsure:

It's a property of the Poisson/Exponential distributions.

30 people an hr implies a Poisson distribution on the number of arrivals during a given period.

It's just a property that the time between Poisson arrivals has an exponential distribution.
 
romsek said:
It's a property of the Poisson/Exponential distributions.

30 people an hr implies a Poisson distribution on the number of arrivals during a given period.

It's just a property that the time between Poisson arrivals has an exponential distribution.

Ah ok!

So do we have the following?

a) $P(X<15)=1-e^{-2\cdot 15}$

b) $P(6\leq X\leq 8)=P(X\leq 8)-P(X\leq 6)=(1-e^{-2\cdot 8})-(1-e^{-2\cdot 6})$

Is that correct? :unsure:
 
mathmari said:
Is that correct? :unsure:

I believe so.
 

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