Chapter Summary

The joint probability distribution p(x, y) of two random variables gives the probability for simultaneous outcomes, p(x, y) = P(X = x, Y = y). The joint probability distribution of independent random variables factors into the product of the marginal distributions, p(x, y) = p(x)p(y). Sums of random variables can be used to model a portfolio of investments. The expected value of a weighted sum of random variables is the weighted sum of the expected values. The variance of a weighted sum of random variables depends on the covariance, a measure of dependence between random variables. For independent random variables, the covariance is zero. The correlation between random variables is a scale-free measure of dependence. Random variables ...

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