Support of Continuous Conditional Density Functions (Probability)

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SUMMARY

The joint probability density function for continuous random variables X and Y is defined as f(x,y) = x + y, with support in the region {0 < x < 1, 0 < y < 1}. The marginal probability density function of X, g(x), is derived by integrating f(x,y) with respect to y, resulting in g(x) = x + (1/2) with support 0 < x < 1. The conditional density function h(y|x) = f(x,y)/g(x) is well-defined and takes non-zero values only in the region {0 < y < 1} when conditioning on a specific value of X. The confusion arises from the relevance of the fixed value of X in determining the support of the conditional density function.

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f(x,y) = x + y is the joint probability density function for continuous random variables X and Y. The support of this function is {0 < x < 1, 0 < y < 1}, which means it takes positive values over this region and zero elsewhere.

g(x) = x + (1/2) is the probability density function of X, derived by integrating f(x,y) with respect to y, over 0 < y < 1. Since we "took y out of the equation", the support of this function should be 0 < x < 1.

Question :

What is the support of the conditional density function h(y|x) = f(x,y)/g(x)?

My guess is that this function is well defined and takes non zero values only over region {0 < x < 1, 0 < y < 1} and so this is the support.

But the book I am using states 0 < y < 1 instead. Is it a typo?
 
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I just realized my mistake :

x is fixed since we are conditioning Y on a particular value of X = x. So the 0 < x < 1 is irrelevant. Or rather, the conditional probability density for a given X = x is a function of y only. So only the value of y matters in defining the support.

I feel like an idiot lol.
 

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