#######Question 2 : Moyennes de toutes les variables
# Charger les données
df <- read_excel("C:/Users/Alioune/Desktop/Projet_statistique/data_mauristartups.xlsx")
# Calculer les moyennes
mean_values <- sapply(df[, c("design", "fonctionnalité", "problèmes_techniques", "prix", "recommandation", "employés")], mean)
print(mean_values)
##               design       fonctionnalité problèmes_techniques 
##             7.460833             5.586667             7.283333 
##                 prix       recommandation             employés 
##             5.768333             6.815000            14.383333
##              design fonctionnalité problèmes_techniques     prix recommandation
## moy        7.460833       5.586667             7.283333 5.768333       6.815000
## ecart_type 1.984278       1.978198             1.629937 1.986466       1.860318
## var        3.937361       3.913266             2.656695 3.946048       3.460782
## IQR        2.450000       2.925000             2.200000 2.650000       2.600000
##             employés
## moy        14.383333
## ecart_type  8.165498
## var        66.675350
## IQR        12.000000

##       recommandation             employés               design 
##            1.0000000           -0.1512397            0.6952829 
##       fonctionnalité problèmes_techniques                 prix 
##            0.2613528            0.6787372            0.7388743
## Warning in cor.test.default(df$recommandation, df$satisfaction, method =
## "spearman"): Cannot compute exact p-value with ties
## 
##  Spearman's rank correlation rho
## 
## data:  df$recommandation and df$satisfaction
## S = 154797, p-value = 1.05e-07
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
##       rho 
## 0.4624725
##   X-squared 
## 0.003812575
## X-squared 
## 0.2083265

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.