On Sums of Random Variables and Independence

Suppose that the density of the sum of two random variables X and Y is given by the convolution of the two marginal densities.Although this condition is stronger than uncorrelatedness of X and Y, it does not imply stochastic independence, as is shown by three examples.A situation for which this fact may be relevant occurs in the construction of chi-squared tests for nested hypotheses.