varian.R

### Bab 7 ###

varians = read.csv(file.choose())
if (ncol(varians) == 1) varians = read.csv2(file.choose())

# Samain nama kolom biar gak typo
colnames(varians) = c("Nilai", "Kelas")

varians$Nilai = as.numeric(gsub(",", ".", as.character(varians$Nilai)))
varians$Kelas = as.factor(varians$Kelas)
varians

##    Nilai Kelas
## 1     70     1
## 2     80     1
## 3     87     1
## 4     77     1
## 5     80     1
## 6     80     2
## 7     85     2
## 8     70     2
## 9     77     2
## 10    85     2
## 11    60     2
## 12    80     2
## 13    70     3
## 14    87     3
## 15    90     3
## 16    77     3
## 17    76     3
## 18    87     3

library(car)

## Loading required package: carData

leveneTest(Nilai ~ Kelas, data = varians)

## Levene's Test for Homogeneity of Variance (center = median)
##       Df F value Pr(>F)
## group  2  0.4267 0.6604
##       15

library(lawstat)

## 
## Attaching package: 'lawstat'

## The following object is masked from 'package:car':
## 
##     levene.test

levene.test(varians$Nilai, varians$Kelas, location="median", correction.method="zero.correction")

## 
##  Modified robust Brown-Forsythe Levene-type test based on the absolute
##  deviations from the median with modified structural zero removal method
##  and correction factor
## 
## data:  varians$Nilai
## Test Statistic = 0.4372, p-value = 0.6557

levene.test(varians$Nilai, varians$Kelas, location="mean", correction.method="zero.correction")

## 
##  Classical Levene's test based on the absolute deviations from the mean
##  ( zero.correction not applied because the location is not set to median
##  )
## 
## data:  varians$Nilai
## Test Statistic = 0.64903, p-value = 0.5366