Combining Exponential Distributions for Concession Stand Wait Times

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In summary, the problem involves finding the mean, variance, and distribution of the total time for a concession stand where customers are served one after the other with exponential wait times. The mean is found by combining the individual mean times, resulting in a lambda of 1/8 and a mean of 8 minutes. The variance is calculated by combining the individual variances, resulting in a variance of 1/64. The resulting distribution is an exponential distribution with a pdf of 1/64e^-x/64.
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rhyno89
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Homework Statement


A concession stand serves customers with each customer starting as soon as the prior one finishes. The wait times are from an exponential distribution with mean = 2 minutes. Therefore the Total time is the summation of xi for i 1 to 4. Find the mean , variance and distribution of T.


Homework Equations





The Attempt at a Solution


I tried combining the pdfs to get the distribution and thought that I could work it from there. My first try was by comibining the mgf but was fairly certain that it would just make it more complicated so I shifted to trying to work with the exponential to the 4th since it was the same distribution. I got .0625e^-2x.

I thought that this was simple enough but this way they it could not have been another exponential distribution since the value for lambda was different throughout the equation.

As of now I was thinking that it is easier than it looks and the mean of this is simply (mu * n) which would give me 8 minutes.
The variance would then be 1/(.5^2) for each one and since they are independant would be 4*4=16

This seems not only way too easy but also way too high for a variance

Any tips to get me on the right track would be very appreaciated
 
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  • #2
what i did was just combine the means since they are independant...resulting in a total mean of 8 minutes. This resulting in a lambda of 1/8 and therefore a variance of 1/64. Finally it would have a pdf of 1/64e^-x/64...

im pretty sure that's right but can anyone clarify?
 

1. What is an exponential pdf?

An exponential pdf (probability density function) is a mathematical function that describes the probability distribution of a continuous random variable that follows an exponential distribution. It is commonly used in statistics and probability to model events that occur randomly over time.

2. How do you combine exponential pdfs?

To combine exponential pdfs, you can use the sum of exponential distributions formula, which states that the resulting pdf will be a linear combination of the individual pdfs. This means that you can simply add the individual exponential pdfs together to get the combined pdf.

3. What is the purpose of combining exponential pdfs?

The purpose of combining exponential pdfs is to model more complex scenarios where multiple events with different exponential distributions are occurring simultaneously. By combining the pdfs, you can get a better understanding of the overall probability distribution for the scenario.

4. Can you combine exponential pdfs with different parameters?

Yes, you can combine exponential pdfs with different parameters. However, the resulting combined pdf will have a different parameter value than the individual pdfs. This new parameter value will depend on the specific parameters of the individual pdfs and their respective weights in the linear combination.

5. Are there any limitations to combining exponential pdfs?

One limitation of combining exponential pdfs is that the resulting combined pdf may not always accurately represent the true probability distribution of the scenario. This is because the linear combination assumes that the individual events are independent, which may not always be the case.

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