diff --git a/Scripts/treatment.R b/Scripts/treatment.R
index 5a8c217d591112f6cd325ae694399904a060216f..acec3c3ccba208218253a2ada72b65e796b2c68d 100644
--- a/Scripts/treatment.R
+++ b/Scripts/treatment.R
@@ -59,25 +59,25 @@ print(xtable(treatment_socio_B, type ="latex"),
       include.rownames = F, file ="Tables/socio_demos_B.tex")
 
 ### Case C
-treatment_socio <- database_full %>% filter(!is.na(Treatment)) %>% group_by(Treatment) %>% 
+treatment_socio <- database_full %>% filter(!is.na(Treatment)) %>% group_by(Treatment_C) %>% 
   summarize_at(c('Gender_female', 'Uni_degree', 'Age', 'HHSize', "Rent_SQ", "Kids_Dummy", "WalkingDistance_SQ",
                  "Naturalness_SQ", "Employment_full", "Z_Mean_NR"),
                ~ round(mean(., na.rm = TRUE), 2))
 
-treatment_socio_C <- database_full %>% filter(!is.na(Treatment_new)) %>% group_by(Treatment_new) %>% 
+treatment_socio_C <- database_full %>% filter(!is.na(Treatment_new)) %>% group_by(Treatment_C) %>% 
   summarize_at(c('Gender_female', 'Uni_degree', 'Age', 'HHSize', "Rent_SQ", "Kids_Dummy", "WalkingDistance_SQ",
-                 "Naturalness_SQ", "Employment_full", "Pensioner"),
+                 "Naturalness_SQ", "Employment_full",  "Z_Mean_NR"),
                ~ round(mean(., na.rm = TRUE), 2))
-
-treatment_socio_C <- treatment_socio_C %>%  mutate(Treatment_name = case_when(
-  Treatment_new == 1 ~ 'Video 1',
-  Treatment_new == 2 ~ 'No Video 1',
-  Treatment_new == 3 ~ 'No Info 2',
-  Treatment_new == 4 ~ 'No Video 2',
-  Treatment_new == 5 ~ 'Video 2',
-  Treatment_new == 6 ~ 'No Treatment 3',
-  TRUE ~ NA_character_
-))
+# 
+# treatment_socio_C <- treatment_socio_C %>%  mutate(Treatment_name = case_when(
+#   Treatment_new == 1 ~ 'Video 1',
+#   Treatment_new == 2 ~ 'No Video 1',
+#   Treatment_new == 3 ~ 'No Info 2',
+#   Treatment_new == 4 ~ 'No Video 2',
+#   Treatment_new == 5 ~ 'Video 2',
+#   Treatment_new == 6 ~ 'No Treatment 3',
+#   TRUE ~ NA_character_
+# ))
 
 # Export table as tex file 
 print(xtable(treatment_socio_C, type ="latex"), 
diff --git a/project_start.qmd b/project_start.qmd
index 67a9f8ca586ef293848423cf8ada8a433004ed41..19e2c9f57deba6a9daf41b85c18b0c2247b2be02 100644
--- a/project_start.qmd
+++ b/project_start.qmd
@@ -118,26 +118,24 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
 ```
 ## Socio Demografics {.smaller}
 
-::: {style="font-size: 37%;"}
+::: {style="font-size: 50%;"}
 ::: panel-tabset
 ### Case A
 
 ```{r}
-library(DT)
-treatment_socio_A <- treatment_socio_A
-datatable(treatment_socio_A)
+kableExtra::kable(treatment_socio_A)
 ```
 
 ### Case C
 
 ```{r}
-library(DT)
-treatment_socio_C <- treatment_socio_C %>% select(-Treatment_new) %>% select(Treatment_name, everything())
-datatable(treatment_socio_C)
+kableExtra::kable(treatment_socio_C)
 ```
 :::
 :::
 
+
+
 ## NR
 
 **Hypotheses:** Individuals with greater Nature Relatedness (NR) are more inclined to autonomously seek information about environmental subjects, such as the impact of urban green spaces on urban heat islands. Consequently, any observed increase in the willingness to pay among the treated group may be attributed to the individuals' higher NR rather than the treatment itself.