diff --git a/doc/src/Regression/Regression.do.txt b/doc/src/Regression/Regression.do.txt
index 18d6bc1d8..2f4b2630a 100644
--- a/doc/src/Regression/Regression.do.txt
+++ b/doc/src/Regression/Regression.do.txt
@@ -269,7 +269,8 @@ meaning that the solution for $\hat{\beta}$ is the one which minimizes the resid
 
 !split
 ===== Simple regression model =====
-Add info about the equations
+We are now ready to write our first program which aims at solving the above linear regression equations. We start with data we have produced ourselves, in this case normally distributed random numbers along the $x$-axis. These numbers define then the value of a function $y(x)=4+3x+N(0,1)$. Thereafter we order the $x$ values and employ 
+
 !bc pycod
 # Importing various packages
 from random import random, seed