diff --git a/notes/sections/3.md b/notes/sections/3.md
index f72de81..2aaadea 100644
--- a/notes/sections/3.md
+++ b/notes/sections/3.md
@@ -188,7 +188,7 @@ The overall minimisation ends when the gradient module is smaller than $10^{-4}$
 The program took 25 of the above iterations to reach the result shown in @eq:Like_res.
 
 The Cramér-Rao bound states that the covariance matrix of parameters estimated
-by MLM is greater than the of the inverse of the Hessian matrix of $-\log(L)$
+by MLM is greater than the the inverse of the Hessian matrix of $-\log(L)$
 at the minimum. Thus, the Hessian matrix was computed
 analytically and inverted by a Cholesky decomposition, which states that
 every positive definite symmetric square matrix $H$ can be written as the