uji normalitas distribusi data

#input data
normalitas = read.table(file.choose(), header = TRUE)
View(normalitas)

#uji nomalitas
x = normalitas$data
summary(x)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    10.0    47.5    85.0    85.0   122.5   160.0

library(nortest)
lillie.test(x)

## 
##  Lilliefors (Kolmogorov-Smirnov) normality test
## 
## data:  x
## D = 0.081375, p-value = 0.9954

library(tseries)

## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo

jarque.bera.test(x)

## 
##  Jarque Bera Test
## 
## data:  x
## X-squared = 0.97512, df = 2, p-value = 0.6141