BAB-6-STATISTIK.R

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### NAMA          : WILDIA NURATNA PUTRI NOVIA           ###
### NIM           : 2502056045                           ###
### MATA KULIAH   : STATISTIKA                           ###
### PROGRAM STUDI : ILMU KOMUNIKASI A ANGKATAN 2025      ###
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###                   MENGERJAKAN BAB 6                  ###
###               UJI NORMALITAS POPULASI                ###
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#Uji Normalitas dengan Uji Kolmogorov-Smirnov 
library(readxl)
simpan=read_excel(file.choose()) #membaca data
simpan

## # A tibble: 16 × 1
##     Data
##    <dbl>
##  1    40
##  2    50
##  3    50
##  4    60
##  5    60
##  6    60
##  7    70
##  8    70
##  9    70
## 10    70
## 11    80
## 12    80
## 13    80
## 14    90
## 15    90
## 16   100

x=simpan$Data

summary(x)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##      40      60      70      70      80     100

library(nortest) 
lillie.test(x)

## 
##  Lilliefors (Kolmogorov-Smirnov) normality test
## 
## data:  x
## D = 0.125, p-value = 0.7235

#Uji Normalitas Populasi dengan Uji Jarque-Bera
library(readxl)
simpan=read_excel(file.choose()) #membaca data
simpan

## # A tibble: 16 × 1
##     Data
##    <dbl>
##  1    40
##  2    50
##  3    50
##  4    60
##  5    60
##  6    60
##  7    70
##  8    70
##  9    70
## 10    70
## 11    80
## 12    80
## 13    80
## 14    90
## 15    90
## 16   100

X=simpan$Data

library(e1071)
a=moment(X, order = 2, center = TRUE)
b=moment(X, order = 4, center = TRUE)
a

## [1] 250

b

## [1] 145000

c=a^2
c

## [1] 62500

kurtosis = b/c
kurtosis

## [1] 2.32

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 = 0.30827, df = 2, p-value = 0.8572

#Uji Normalitas Populasi dengan Quantile-Quantile Plot (Q-Q Plot)
library(readxl)
simpan=read_excel(file.choose()) #membaca data
simpan

## # A tibble: 16 × 1
##     Data
##    <dbl>
##  1    40
##  2    50
##  3    50
##  4    60
##  5    60
##  6    60
##  7    70
##  8    70
##  9    70
## 10    70
## 11    80
## 12    80
## 13    80
## 14    90
## 15    90
## 16   100

X=simpan$Data

qqnorm(x)
qqline(x)