library(datasets)
#load data
data("mtcars")
#membangun model regresi linear
model <- lm(mpg ~ wt+drat+hp, data = mtcars)
#melihat ringkasal model
summary(model)
##
## Call:
## lm(formula = mpg ~ wt + drat + hp, data = mtcars)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.3598 -1.8374 -0.5099 0.9681 5.7078
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 29.394934 6.156303 4.775 5.13e-05 ***
## wt -3.227954 0.796398 -4.053 0.000364 ***
## drat 1.615049 1.226983 1.316 0.198755
## hp -0.032230 0.008925 -3.611 0.001178 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.561 on 28 degrees of freedom
## Multiple R-squared: 0.8369, Adjusted R-squared: 0.8194
## F-statistic: 47.88 on 3 and 28 DF, p-value: 3.768e-11
#melihat residuals
residuals <- model$residuals
head(residuals)
## Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
## -2.6910398 -1.8679115 -2.3265904 0.9539327
## Hornet Sportabout Valiant
## 0.9621452 -1.1995550
residuals
## Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
## -2.69103977 -1.86791148 -2.32659041 0.95393269
## Hornet Sportabout Valiant Duster 360 Merc 240D
## 0.96214517 -1.19955505 -0.85899549 1.34099488
## Merc 230 Merc 280 Merc 280C Merc 450SE
## 0.30401886 -1.45742317 -2.85742317 0.98611212
## Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
## 0.78860774 -1.14999455 -0.17303522 0.59787942
## Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla
## 4.75486594 5.64437305 -0.06799697 5.70783262
## Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
## -2.78735818 -2.15550966 -3.35975468 -1.82727313
## Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
## 2.88251996 -0.31103478 -0.70881110 3.44226261
## Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E
## -1.66899847 -0.95965686 2.20877479 -2.14595772
#melakukan uji normalitas residual (shapiro-walk test)
shapiro.test(model$residuals)
##
## Shapiro-Wilk normality test
##
## data: model$residuals
## W = 0.91718, p-value = 0.01744
#uji normalitas residual jugaaa
library(nortest)
lillie.test(model$residuals) #kolmogorov
##
## Lilliefors (Kolmogorov-Smirnov) normality test
##
## data: model$residuals
## D = 0.12395, p-value = 0.2409
#uji autokorelasi
library(lmtest)
## Warning: package 'lmtest' was built under R version 4.3.3
## Loading required package: zoo
## Warning: package 'zoo' was built under R version 4.3.2
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
dwtest(model)
##
## Durbin-Watson test
##
## data: model
## DW = 1.706, p-value = 0.1417
## alternative hypothesis: true autocorrelation is greater than 0
# uji multikolinearitas
library(car)
## Warning: package 'car' was built under R version 4.3.2
## Loading required package: carData
## Warning: package 'carData' was built under R version 4.3.2
vif(model)
## wt drat hp
## 2.869445 2.033837 1.769308
#uji heterokedastisitas
bptest(model)
##
## studentized Breusch-Pagan test
##
## data: model
## BP = 1.5987, df = 3, p-value = 0.6597