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Probability Distribution Functions

With a PDF we can compute expectation values of selected quantities such as \begin{equation*} \langle x^k\rangle=\sum_{i=1}^{N}x_i^kp(x_i), \end{equation*} if we have a discrete PDF or \begin{equation*} \langle x^k\rangle=\int_a^b x^kp(x)dx, \end{equation*} in the case of a continuous PDF. We have already defined the mean value \mu and the variance \sigma^2 .