Probability of 1 Phone Call: Solve w/ Exponential Distrib.

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Homework Help Overview

The problem involves determining the probability of receiving exactly one phone call in a night, based on an average rate of one call per night. The context relates to probability distributions, specifically the exponential and possibly the gamma distribution.

Discussion Character

  • Exploratory, Assumption checking, Problem interpretation

Approaches and Questions Raised

  • Participants discuss the use of the exponential distribution and its relationship to the gamma distribution. There is mention of deriving the probability without relying on a specific distribution, suggesting a binomial approach with a large number of potential callers. Some participants explore the connection to the Poisson approximation.

Discussion Status

The discussion is active, with participants exploring different methods to derive the probability. There are suggestions to approach the problem from various angles, including binomial and Poisson distributions, but no consensus has been reached on the best method yet.

Contextual Notes

Participants note the absence of specific assumptions in the problem prompt, which may affect the approach taken. There is also a reference to the level of complexity expected in the exercise, indicating it may be beyond introductory material.

Providence88
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Homework Statement



Suppose that on average, I will receive one phone call every night. Under reasonable assumptions (not given in this question prompt), show that the probability of receiving exactly one phone call, tonight, is e^-1.

Homework Equations



Possibly the gamma distribution function or exponential distribution function, but I'm not sure, as this problem arises out of material far out of the introductory distribution functions.

That is,

f(y) = \frac{1}{\Gamma(\alpha)\beta^{\alpha}} * y^{\alpha-1}e^{\frac{-y}{\beta}

is a gamma distribution for y>0. An exponential distribution, of course, is just a gamma with alpha = 1.

The Attempt at a Solution



Well, I thought that if \beta = 1, then you simply compute f(1), where y is the number of calls in a day. This, however, seems too easy, considering that this class is Mathematical Statistics 2, and we learned that sort of thing in M.S. 1.

Thanks!
 
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I think you are supposed to derive the probability without using a given arbitrary distribution. I would guess that the reasonable assumption is that there is a pool of N people that might call you, each one with probability p. So just use the binomial distribution. Now let N go to infinity.
 
Dick said:
I think you are supposed to derive the probability without using a given arbitrary distribution. I would guess that the reasonable assumption is that there is a pool of N people that might call you, each one with probability p. So just use the binomial distribution. Now let N go to infinity.
I guess you're talking about Poisson approximation? I had to look that one up. It's mentioned in the book, but not under that term. Very clever. I'll have to try that out.
 
Yes, I am. But you shouldn't need to look it up. I think they want you to derive it from the binomial distribution. That would be worthy of a Stat 2 exercise.
 
Right. I'll try and derive it without looking back at the book. Thanks!
 

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