- #1
danago
Gold Member
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A group of students wish to determine how long, on average, customers are waiting in line at a supermarket before being served.
The students conduct trials and record the times taken. They found that they were kept waiting for an average of 7 minutes.
If a customer goes to that same supermarket, what is the probability they will be waiting more than 7 minutes in line before being served?
Originally, i would have thought to model this situation using a Gaussian distribution, but i am not given a standard deviation to work with, only a mean.
My next thought was to use an exponential distribution function.
[tex]
\begin{array}{c}
P(x > 7) = \int_7^\infty {\frac{{e^{ - \frac{x}{7}} }}{7}} dx \\
= \mathop {\lim }\limits_{a \to \infty } \int_7^a {\frac{{e^{ - x/7} }}{7}} dx \\
= \mathop {\lim }\limits_{a \to \infty } \left[ { - e^{ - x/7} } \right]_7^a \\
= \mathop {\lim }\limits_{a \to \infty } (e^{ - 1} - e^{ - a/7}) \\
= e^{ - 1} \approx 0.368 \\
\end{array}
[/tex]
Does that look right?
Also, if i was given more information, would a gaussian distribution have been suitable?
Thanks,
Dan.
The students conduct trials and record the times taken. They found that they were kept waiting for an average of 7 minutes.
If a customer goes to that same supermarket, what is the probability they will be waiting more than 7 minutes in line before being served?
Originally, i would have thought to model this situation using a Gaussian distribution, but i am not given a standard deviation to work with, only a mean.
My next thought was to use an exponential distribution function.
[tex]
\begin{array}{c}
P(x > 7) = \int_7^\infty {\frac{{e^{ - \frac{x}{7}} }}{7}} dx \\
= \mathop {\lim }\limits_{a \to \infty } \int_7^a {\frac{{e^{ - x/7} }}{7}} dx \\
= \mathop {\lim }\limits_{a \to \infty } \left[ { - e^{ - x/7} } \right]_7^a \\
= \mathop {\lim }\limits_{a \to \infty } (e^{ - 1} - e^{ - a/7}) \\
= e^{ - 1} \approx 0.368 \\
\end{array}
[/tex]
Does that look right?
Also, if i was given more information, would a gaussian distribution have been suitable?
Thanks,
Dan.
Last edited: