Update toy_document_en.Rmd

module2/exo1/toy_document_en.Rmd

@@ -11,14 +11,14 @@ knitr::opts_chunk$set(echo = TRUE)
 ```
 
 ## Asking the maths library
-My computer tells me that π is *approximatively*
+My computer tells me that $\pi$ is *approximatively*
 
-```{r cars}
+```{r}
 pi
 ```
 
-##Buffon's needle
-Applying the method of [Buffon's neddle](https://en.wikipedia.org/wiki/Buffon%27s_needle_problem), we get the *approximation*
+## Buffon's needle
+Applying the method of [Buffon's needle](https://en.wikipedia.org/wiki/Buffon%27s_needle_problem), we get the __approximation__
 
 ```{r}
 set.seed(42)
@@ -28,8 +28,8 @@ theta = pi/2*runif(N)
 2/(mean(x+sin(theta)>1))
 ```
 
-##Using a surface fraction argument
-A method that is easier to understand and does not make use of the sin function is based on the fact that if X∼U(0,1) and Y∼U(0,1), then P[X2+Y2≤1]=π/4 (see [“Monte Carlo method”](https://en.wikipedia.org/wiki/Monte_Carlo_method) on Wikipedia). The following code uses this approach:
+## Using a surface fraction argument
+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)
@@ -40,7 +40,7 @@ library(ggplot2)
 ggplot(df, aes(x=X,y=Y,color=Accept)) + geom_point(alpha=.2) + coord_fixed() + theme_bw()
 ```
 
-It is therefore straightforward to obtain a (not really good) approximation to π by counting how many times, on average, X2+Y2 is smaller than 1 :
+It is then straightforward to obtain a (not really good) approximation to $\pi$ by counting how many times, on average, $X^2+Y^2$ is smaller than 1 :
 ```{r}
 4*mean(df$Accept)
 ```
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