Are those solutions equivalent?

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Discussion Overview

The discussion revolves around the probability calculations for devices connected in parallel versus in series, specifically focusing on the lifetimes of two components represented as random variables. Participants explore the implications of using different probability approaches, such as the maximum and minimum of the random variables, in determining the overall probability of the device functioning within a specified time frame.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant notes that for devices in parallel, the probability of the device working for a year is calculated using the union of the individual probabilities, P(A or B).
  • Another participant raises a concern about the difference in results when calculating the probability of the maximum of two random variables versus the union of their probabilities.
  • There is a question about whether P(a
  • A participant suggests that for parallel problems, one should consider the minimum of the two random variables instead of the maximum, as it aligns better with the concept of at least one component functioning.
  • Another participant proposes that the interpretation of the probability expressions may differ based on the context of the problem, particularly in distinguishing between parallel and series configurations.

Areas of Agreement / Disagreement

Participants express differing views on the equivalence of the probability approaches for parallel and series configurations. There is no consensus on whether the maximum or minimum should be used for parallel problems, and the discussion remains unresolved regarding the best method to calculate the probabilities.

Contextual Notes

Participants highlight the importance of understanding the context of the problem when applying probability concepts, particularly regarding the independence of the random variables and the implications of using maximum versus minimum values.

fateswarm
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On my studying material I noticed that for "devices in parallel" problems, a question of the type "Find the probability the device works for 1 year" is dealt with P(A or B) where P(A), P(B) are the probabilities of each of the instruments working for one year, which is something I intuitively understand.

Now, when I went to a random variables chapter problem, for two random variables X and X, given their probability density function, for two devices in parallel where each device's life is represented by each random variable, the question "find the probability the device works for between 1 and 2 years" is dealt with the probability of max{X, Y} satisfying that criteria which appears to give a different result than the union of the corresponding probabilities!

I'll try to translate the actual problem: "The lifetimes X,Y (in hours) of two components are random variables with common probability density function fx,y(x,y) = e^(-x-y) with x,y>0. Calculate the probability the lifetime of the machine is between 1 and 2 hours when the components are connected in parallel." (it also asks for a connection in series). (It is also given from a previous exercise that the random variables are independent.)


My understanding is that if I use fx and fy and find the components probabilities separately and then calculate their union, the result would be the same. But in this case the result is: P(1<X<2)=P(1<Y<2)=0.2325 with P(1<X<2 or 1<Y<2) = 0.4109

While if I actually find the function for max{X,Y}, it's P(max{X,Y}<z) = P(X<z,Y<z) = P(X<z)P(Y<z) = Fx(x)Fy(y) which gives a different result.

Are the approaches equivalent?
 
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P(1<X<2)=P(1<Y<2)=0.2325 with P(1<X<2 or 1<Y<2) = 0.4109
That includes the case where X breaks between 1 and 2, but Y breaks afterwards (and vice versa) - so the device works longer than 2.
 
mfb said:
That includes the case where X breaks between 1 and 2, but Y breaks afterwards (and vice versa) - so the device works longer than 2.

How? Aren't X, Y restricted to be examined between the times 1 and 2? How could X, or Y go beyond those time frames?
 
I currently wonder if P(a<max{X,Y}<b) is equivalent to P(a<X<b or a<Y<b) to begin with. They seem to answer two different questions. The first being "the probability of the one with the maximum value being between those two values" and the latter "the probability of either being between those two values" effectively making the latter the right answer.

edit: Then again, I can't be certain since intuitively, either expression seems to cover it.

edit: The main indication is that I know P(A or B) was accepted in simpler problems.
 
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I think I figured it out, initially numerically and not intuitively, since I get the same result:

It appears that for the PARALLEL problem one has to test the MIN between X, and Y rather than the max. That way the result more conveniently is, for a simpler example of "less than 1 hour": P(min{X,Y}<1} = 1-P(min{X,Y}>1) =1-P(X>1,Y>1)=1-(1-P(X<1)(1-P(Y<1)) which is the same with the initial union of the simpler solutions.

If one goes with the MAX, the answer appears to be suitable for the intersection of the events and a problem of the components being in series. Now why would those problems work that way intuitively? I keep looking at it and there is little intuition that would e.g. point at the "min" of the two being suitable for the parallel problem, unless we're talking about an abstract concept of "I'm looking for at-a-minimum one of those two working in this interval" which is weird since it doesn't examine the interval itself but the existence of the random variables themselves in it, but I guess it's closer to reality.

edit: Or I guess, one I could say "I am satisfied with the minimum of those two being in this interval in order to answer the parallel problem", however "even the maximum of those two must satisfy the interval in order for them to work in series". Weird stuff when first seen but I guess it makes sense.
 
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The most intuitive way I found to look at it mathematically is to read the symbolism in reverse: e.g. P(y>max{X,Y}) for the serial problem. That way "y must be larger even than the larger of the two, hence both must be large enough [which is what I want in a serial situation]".
 

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