Moment Generating Function Explained

<p>The n-th moment is&nbsp;<strong>E(X^n)</strong>.</p> <p>We are pretty familiar with the first two moments, the mean&nbsp;<strong>&mu; =</strong>&nbsp;<strong>E(X)</strong>&nbsp;and the variance&nbsp;<strong>E(X&sup2;) &minus; &mu;&sup2;</strong>. They are important characteristics of&nbsp;<strong>X</strong>.<strong>&nbsp;</strong>The mean is<strong>&nbsp;</strong>the average value and the variance is how spread out the distribution is. But there must be&nbsp;<strong>other</strong>&nbsp;<strong>features</strong>&nbsp;<strong>as well</strong>&nbsp;that also define the distribution.&nbsp;For example, the third moment is about the asymmetry of a distribution. The fourth moment is about how heavy its tails are.</p> <p><a href="https://towardsdatascience.com/moment-generating-function-explained-27821a739035"><strong>Read More</strong></a></p>