Joint probability density function


Let X1 and X2 be continuous random variables with the joint probability density function, fX1,X2(x1,x2), -inf.

Show that fY1(y1)=integral from -inf to inf of fX1,X2(y1-y2,y2)dy2, which is sometimes called the convolution formula.

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Basic Statistics: Joint probability density function
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