Generalized-Linear-Models.md

@@ -30,7 +30,16 @@ When constructing a generalized linear model, three major decisions must be made
     psychological and behavioral research the most important distributions are:
 
     - Continuous variables: 
-      * Normal 
+      * Normal: <a href="https://www.codecogs.com/eqnedit.php? 
+                latex=f(y;&space;\mu,&space;\sigma^2)=\frac{1}{ 
+                \sqrt{2\pi\sigma^2}}exp(\frac{-(y-\mu)^2}{2\sigma^2})" target="_blank"><img 
+                src="https://latex.codecogs.com/svg.latex? 
+                f(y;&space;\mu,&space;\sigma^2)=\frac{1}{\sqrt{2\pi\sigma^2}}exp(\frac{-(y- 
+                \mu)^2}{2\sigma^2})" title="f(y; \mu, \sigma^2)=\frac{1} 
+                {\sqrt{2\pi\sigma^2}}exp(\frac{-(y-\mu)^2}{2\sigma^2})" /></a>    for <a 
+                href="https://www.codecogs.com/eqnedit.php?latex=-\infty<y<\infty" 
+                target="_blank"><img src="https://latex.codecogs.com/svg.latex?- 
+                \infty<y<\infty" title="-\infty<y<\infty" /></a>
       * Gamma 
       * Inverse Gaussian 
     - Discrete variables: