diff --git a/Practical_c.Rmd b/Practical_c.Rmd
index fd258917c7cfae9d29745d26e6502ff51400d502..a6a7d918e3a905da61e308c4abc67a4fe1fde21f 100644
--- a/Practical_c.Rmd
+++ b/Practical_c.Rmd
@@ -162,7 +162,11 @@ str(morpho_data)
 str(yeast_data)
 ```
 
-- `yeast_av_data`: a data frame containing the average (over all cells) of the morphological measures for each strain and each cell cycle phase with the corresponding genotype (same columns as `yeast_data`)
+- `yeast_av_data`: a data frame containing the average (over all cells) of the morphological measures for each strain and each cell cycle phase with the corresponding genotype (same columns as `yeast_data`). More details with:
+
+```{r, eval=F}
+str(yeast_av_data)
+```
 
 - `strain_id`: a data frame containing the identification of the different strains (including other not present in `morpho_data` and `gt_data`)
 
@@ -649,7 +653,14 @@ What can you say about this figure? What could be the problem? especially regard
 <details><summary>Solution</summary>
 <p>
 
-In a non negligible number of samples, the $H_0$ hypothesis was rejected (p-value $\leq\alpha$) whereas it is true. In this case, we find a significant result $\mu\ne 0$ despite being wrong.
+In a non negligible number of samples, the null hypothesis was rejected (p-value $\leq\alpha$) whereas it is true. In this case, we find a significant result $\mu\ne 0$ despite being wrong.
+
+However, in the majority of the studies, the null hypothesis is correctly not rejected.
+
+**Important:**
+
+- confirm a detected effect with additional experiments/studies
+- the more (independent) studies, the lower risk of incorrect conclusion
 
 </p>
 </details>