Fida-Ayu-Dhiya-Nasywa–bab-7–.R

Modern

2026-09-27

qf(.95, df1=2, df2=15)

## \[1\] 3.68232

varians=read.csv(“varians.csv”)
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(varians$Nilai, varians$Kelas)

## Warning in leveneTest.default(varians$Nilai, varians$Kelas): varians$Kelas
## coerced to factor.

## 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

data(varians)

## Warning in data(varians): data set ‘varians’ not found

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