Generalized-Linear-Models.md

@@ -26,7 +26,7 @@ When constructing a generalized linear model, three major decisions must be made
 
 1. **Specifying the Random Component:** 
     An appropriate probability distribution for the response variable must be chosen. This 
-    should be any member from the *natural exponential family* distributions: 
+    should be any member from the *natural exponential family* distributions:
     - Continuous variables: 
       * Normal 
       * Gamma 
@@ -35,14 +35,16 @@ When constructing a generalized linear model, three major decisions must be made
       * Poisson 
       * Bernoulli 
       * Binomial 
-
 2. **Specifying the Systematic Component (Linear Predictor):**
     A linear combination of predictor variables should be constructed as the linear 
     predictor of the model. 
-
 3. **Choosing a Link Function:** 
-    Choosing an appropriate function which maps the mean of the response variable onto the 
-    linear predictor.
+    An appropriate function must be chosen which maps the mean of the response variable 
+    onto the linear predictor. This function should be chosen in such a way to ensure that 
+    the predicted means are in the permissible range. 
+
+
+