Density function of product of random variables

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To find the density function of the product of two independent random variables Z = XY, where f(x) and f(y) are the density functions of X and Y, one can start with the cumulative distribution function P(Z ≤ z). This can be expressed as the expected value E_Y[P(XY ≤ z | Y = y)]. The discussion highlights that the approach is valid regardless of whether X and Y have the same distribution. The initial attempt using logs and convolution was noted as ineffective. A focus on the conditional probability approach is suggested for further development of the solution.
khotsofalang
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suppose you have two random variables X and Y which are independent,
we want to form a new random variable Z=XY, if f(x) and f(y) are density functions
of X and Y respectively what is the density function of Z?

I tried taking logs and applying convolution, but it did not really work
 
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It isn't clear to me from your writing whether X and Y have the same distribution - you used the same name for their densities - but think about this start: it will work whether they are identically distributed or not. Start with this
<br /> P(Z \le z) = E_Y \left[P\left( XY \le z \mid Y = y\right) \right]<br />

and see what develops.
 
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