Ten phones are linked by only one line to the network. Each phone

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The discussion revolves around determining the probability of k phones simultaneously needing a single network line, with each phone requiring an average of 12 minutes per hour. Participants debate whether this scenario follows a binomial or Poisson distribution, with some suggesting that the Poisson process is more appropriate due to the independence of calls and the time aspect involved. The average rate of line usage is calculated as 12/60, indicating the likelihood of any phone using the line at a given time. The conversation also touches on the M/M/1 queue model, emphasizing the need for clarity on the rate of calls and their distribution. Overall, the complexity of the problem highlights the nuances in applying statistical models to real-world scenarios.
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Ten phones are linked by only one line to the network. Each phone needs to log on average 12mins an hour to the network. calls made by different phones are independent of each other. They can't simultaneously call.

What is the probability that k phones (k=0,1,2...10) simultaneously need the line? what is the most likely number of phones requiring the line at one time?

Is this a binomial distribution?

if so, does P(X=k) = (10 choose k)(.2^k)(.8^(10-k)) ??

and also would E[X] = 2?

OR is this a Poisson (or other :S) distribution?

Any help as always is greatly appreciated :)
 
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Personally I would use Poisson, esspecialy as it involves time you may want to use a Poisson process. The nice thing about Poisson is independent Poisson processes do not jump at the same time and you can add Poisson processes very easily.

It looks like a M/M/1 queue.
 


So if i was to use a Poisson distribution would my parameter be the average? which is 2?
 


Is there not a rate of calls? The rate should be the rate of people calling in.
 


So by rate you mean 12/60 (12 minutes an hour)?
 


No I mean the rate of calls being made or the line requested.
 


Focus said:
No I mean the rate of calls being made or the line requested.

I don't really know what you mean by this. On average the likely hood of anyone line being used is (12/60)? Hmmm now I'm really lost >.<
 


forty said:
I don't really know what you mean by this. On average the likely hood of anyone line being used is (12/60)? Hmmm now I'm really lost >.<

Sorry I think I confused myself here. The callers need 12mins each per hour right? How is their requests distributed? Do they have Poisson arrival then get served for 12 mins or can they call in for 2 mins then hang up and phone again after a while and spend 10 mins?
 


So... I think what you are getting at is that its a Binomial distribution with the probability being a poisson distribution? if not I'm completely lost :(
 
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Sorry what I am trying to get at is this; if you have one line and people calling in with Poisson with rate \lambda and say they take an exponential time on the line with parameter \mu then you have a M/M/1 queue. Your question looks very similar to this but it depends on the rate they request the line at. The exponential parameter looks like 5 as they need on average 12 mins on the network, but I don't understand what rate they are calling with.
 
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