How to use the DiscreteRandomVariable class?

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This class seems to be in pretty bad shape. I guess that we would better get rid of it. Moreover, for defining two random variables you need a common probability space. And the law of X*Y highly depends on the correlations between X and Y. Were you thinking about the independent case?

@vdelecroix Yes, I was thinking about the independent case, For example, suppose X is a discrete random variable with the following distribution: {10: 0.3, 20: 0.7} and Y is discrete random variable with the following distribution: {30: 0.4, 40: 0.6}. Then, Z=X*Y is a discrete random variable with the following distribution: {300: 0.12, 600: 0.28, 400: 0.18, 800: 0.42}. It seems quite straightforward to implement.

Sure you can do

sage: X = {10: 0.3, 20: 0.7}
sage: Y = {30: 0.4, 40: 0.6}
sage: Z = defaultdict(lambda:0.0)
sage: for x,px in X.iteritems():
....:    for y,py in Y.iteritems():
....:         Z[x*y] += px*py
sage: Z
defaultdict(<function <lambda> at 0x7f3deebbb140>,
    {400: 0.180000000000000,
    800: 0.420000000000000,
    300: 0.120000000000000,
    600: 0.280000000000000})