diff --git a/module2/exo2/exercice_en.Rmd b/module2/exo2/exercice_en.Rmd
index 13b258ddd0da29bc3bf08c64b6a1db742f6d5409..03d34cab0d7e24d4eab27c70cb29f149a79d2b98 100644
--- a/module2/exo2/exercice_en.Rmd
+++ b/module2/exo2/exercice_en.Rmd
@@ -1,7 +1,7 @@
 ---
-title: "Your title"
-author: "Your name"
-date: "Today's date"
+title: "R Statistics"
+author: "Jhouben Cuesta R."
+date: "20/05/2021"
 output: html_document
 ---
 
@@ -10,24 +10,33 @@ output: html_document
 knitr::opts_chunk$set(echo = TRUE)
 ```
 
-## Some explanations
-
-This is an R Markdown document that you can easily export to HTML, PDF, and MS Word formats. For more information on R Markdown, see <http://rmarkdown.rstudio.com>.
-
-When you click on the button **Knit**, the document will be compiled in order to re-execute the R code and to include the results into the final document. As we have shown in the video, R code is inserted as follows:
-
-```{r cars}
-summary(cars)
+## Defining the dataset
+```{r}
+library(stats)
+Data = c(14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0)
+Data
 ```
 
-It is also straightforward to include figures. For example:
-
-```{r pressure, echo=FALSE}
-plot(pressure)
+## Computing the mean
+```{r}
+mean(Data)
 ```
 
-Note the parameter `echo = FALSE` that indicates that the code will not appear in the final version of the document. We recommend not to use this parameter in the context of this MOOC, because we want your data analyses to be perfectly transparent and reproducible.
+## Computing the minimum
+```{r}
+min(Data)
+```
+## Computing the maximum
+```{r}
+max(Data)
+```
 
-Since the results are not stored in Rmd files, you should generate an HTML or PDF version of your exercises and commit them. Otherwise reading and checking your analysis will be difficult for anyone else but you.
+## Computing the median
+```{r}
+median(Data)
+```
 
-Now it's your turn! You can delete all this information and replace it by your computational document.
+## Computing the standard deviation
+```{r}
+sqrt(var(Data))
+```