Sum of two independent uniform random variables

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SUMMARY

The discussion focuses on the sum of two independent uniform random variables, specifically addressing the limits of integration for the probability density function. The key point is the necessity of the limits 1 < z < 2, derived from the conditions of the integrand ∫ f(z-y) dy. The conditions dictate that for valid values of y, both 0 < y < 1 and 0 < z - y < 1 must hold true, leading to the conclusion that the limits are essential for accurate probability calculations.

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Pixel08
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Hi,

http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/Chapter7.pdf (see page 8, sum of two independent random variables).

I don't understand why they had to go further into the limits, 1 < z < 2. Why do they have to do that? And also, where did they get it from?

Can someone explain why? I've been looking at it for several hours now! :(
 
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Hi Pixel08! :smile:
Pixel08 said:
I don't understand why they had to go further into the limits, 1 < z < 2. Why do they have to do that?

In ∫ f(z-y) dy, the integrand is 0 unless 0 < y < 1 and 0 < z - y < 1

The second condition is the same as y < z and y > z - 1

If z < 1, we can ignore the last condition (because z - 1 < 0), so that's 0 < y < 1 and y < z, ie 0 < y < z

If z > 1, we can ignore y < z (because y < 1 anyway), so that's 0 < y < 1 and y > z - 1, ie z - 1 < y < 1 :wink:
 

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