Moment Generating Function Explained
<p>The n-th moment is <strong>E(X^n)</strong>.</p>
<p>We are pretty familiar with the first two moments, the mean <strong>μ =</strong> <strong>E(X)</strong> and the variance <strong>E(X²) − μ²</strong>. They are important characteristics of <strong>X</strong>.<strong> </strong>The mean is<strong> </strong>the average value and the variance is how spread out the distribution is. But there must be <strong>other</strong> <strong>features</strong> <strong>as well</strong> that also define the distribution. 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>