diff --git a/module2/exo1/toy_document_en.Rmd b/module2/exo1/toy_document_en.Rmd
index aaf8cc31579bca60970c56da778099a0841b322c..00ce73455b541df7622026c0b73a367f913330f2 100644
--- a/module2/exo1/toy_document_en.Rmd
+++ b/module2/exo1/toy_document_en.Rmd
@@ -31,7 +31,6 @@ theta = pi/2*runif(N)
 A method that is easier to understand and does not make use of the $\sin$ function is based on the fact that if $X\sim U(0,1)$ and $Y\sim U(0,1)$, then $P[X^2+Y^2\leq 1] = \pi/4$ (see ["Monte Carlo method" on Wikipedia](https://en.wikipedia.org/wiki/Monte_Carlo_method)). The following code uses this approach:
 
 ```{r}
-
 set.seed(42)
 N = 1000
 df = data.frame(X = runif(N), Y = runif(N))
@@ -44,6 +43,5 @@ It is then straightforward to obtain a (not really good) approximation to $\pi$
 1:
 
 ```{r}
-
 4*mean(df$Accept)
 ```
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