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We do so by analytically determining the second moment of the empirical correlation coefficient\n  \\beqn \\theta := \\frac{\\int_0^1W_1(t)W_2(t) dt - \\int_0^1W_1(t) dt \\int_0^1 W_2(t) dt}{\\sqrt{\\int_0^1 W^2_1(t) dt - \\parens{\\int_0^1W_1(t) dt}^2} \\sqrt{\\int_0^1 W^2_2(t) dt - \\parens{\\int_0^1W_2(t) dt}^2}}, \\eeqn of two {\\em independent} Wiener processes, $W_1,W_2$. 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The problem is to mathematically confirm Yule's 1926 empirical finding of \"nonsense correlation\" (\\cite{Yule}). We do so by analytically determining the second moment of the empirical correlation coefficient\n  \\beqn \\theta := \\frac{\\int_0^1W_1(t)W_2(t) dt - \\int_0^1W_1(t) dt \\int_0^1 W_2(t) dt}{\\sqrt{\\int_0^1 W^2_1(t) dt - \\parens{\\int_0^1W_1(t) dt}^2} \\sqrt{\\int_0^1 W^2_2(t) dt - \\parens{\\int_0^1W_2(t) dt}^2}}, \\eeqn of two {\\em independent} Wiener processes, $W_1,W_2$. 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