Recent content by judoudo

just concerning the first part of your question, for two independent random variables X and Y with distribution functions F and G, the distribution function H of max(X,Y) is simply given by the product of F and G H(c)=P(max(X,Y)<=c)=P(X<=c and Y<=c)=P(X<=c)P(Y<=c)=F(c)G(c) differentiating that...

i have a vaguely related question... consider random variables X and Y with E[X]=E[Y]=0 E[X^2]=E[Y^2] (ie the same standard deviation) and for n>=3 E[X^n]>=E[Y^n]>=0 is there a way to conclude that E[|X|]>=E[|Y|] ?

the joint density function is simply the product of the individual density functions see here under independence: http://en.wikipedia.org/wiki/Probability_density_function in that article you also find the correct formula for the density of X+Y, what you have there seems to be the formula for...