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1.4: Continuous Probability Distributions

  • Page ID
    15723
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    Suppose that the variable \(u\) can take on a continuous range of possible values. In general, we expect the probability that \(u\) takes on a value in the range \(u\) to \(u+du\) to be directly proportional to \(du\), in the limit that \(du\rightarrow 0\). In other words, \[P(u\in u:u+du) = P(u)\,du,\] where \(P(u)\) is known as the probability density. The earlier results (1.2.4), (1.3.4), and (1.3.11) generalize in a straightforward manner to give: \[\begin{aligned} 1&= \int_{-\infty}^\infty P(u)\,du,\\[0.5ex] \langle u\rangle &= \int_{-\infty}^\infty P(u)\,u\,du,\\[0.5ex] \left\langle({\mit\Delta} u)^2\right\rangle &= \int_{-\infty}^\infty P(u)\, (u-\langle u\rangle)^2\,du = \left\langle u^{\,2}\right\rangle-\langle u\rangle^2,\end{aligned}\] respectively.

    Contributors and Attributions

    • Richard Fitzpatrick (Professor of Physics, The University of Texas at Austin)

      \( \newcommand {\ltapp} {\stackrel {_{\normalsize<}}{_{\normalsize \sim}}}\) \(\newcommand {\gtapp} {\stackrel {_{\normalsize>}}{_{\normalsize \sim}}}\) \(\newcommand {\btau}{\mbox{\boldmath$\tau$}}\) \(\newcommand {\bmu}{\mbox{\boldmath$\mu$}}\) \(\newcommand {\bsigma}{\mbox{\boldmath$\sigma$}}\) \(\newcommand {\bOmega}{\mbox{\boldmath$\Omega$}}\) \(\newcommand {\bomega}{\mbox{\boldmath$\omega$}}\) \(\newcommand {\bepsilon}{\mbox{\boldmath$\epsilon$}}\)

    This page titled 1.4: Continuous Probability Distributions is shared under a not declared license and was authored, remixed, and/or curated by Richard Fitzpatrick.

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