Show pageDiscussionOld revisionsBacklinksBack to top This page is read only. You can view the source, but not change it. Ask your administrator if you think this is wrong. ====== Normal Distribution ====== a.k.a. Gaussian Distribution, Bell Curve, whatever. $$\mathcal{Norm}(\mathbf{X}=x; \mu, \sigma) = \frac{1}{\sigma\sqrt{2\pi}}\exp{\biggl(-\frac{(x-\mu)^2}{2\sigma^2}\biggr)}$$ === Sum of Normals === Normal Distributions have the favorable quality that their parameters add in quadrature: Given $\mathcal{Norm_A}(\mu_A, \sigma_A)$ & $\mathcal{Norm_B}(\mu_B, \sigma_B)$\\ \\ Then, $\mathcal{Norm_A}+\mathcal{Norm_B} = \mathcal{Norm}\biggl(\mu_A+ \mu_B, \sqrt{\sigma_A^2 + \sigma_B^2}\biggr)$