podatki <- read.table("./Avtomobili.csv", header = TRUE, sep = ";", dec = ",", encoding = "UTF-8")
head(podatki)## znamka tip sedezi ccm kw km vrtljajimax navor vrtljajinav Motor dolzina sirina visina medosna teza_kg
## 1 Alfa Romeo 1642,0TS 5 1995 107 146 5800 187 5000 Bencin 455 176 139 266 1380
## 2 Alfa Romeo spyder2,0 2 1969 110 150 6200 187 4000 Bencin 429 178 132 254 1370
## 3 Alfa Romeo 1552,0TS 5 1969 110 150 6200 187 4000 Bencin 444 173 143 254 1300
## 4 Alfa Romeo GTV2,0 2 1969 110 150 6200 187 4000 Bencin 429 178 132 254 1370
## 5 Alfa Romeo 1452 5 1969 110 150 6200 187 4000 Bencin 410 171 143 254 1240
## 6 Alfa Romeo 1551,8TS 5 1747 103 140 6300 165 4000 Bencin 445 173 144 254 1270
## tezadov_kg pospesek hitrost poraba_120 cena poraba_90 pogon
## 1 1805 9.9 210 8.3 50170 6.5 1
## 2 1630 8.4 210 7.8 56390 6.2 1
## 3 1840 9.0 210 8.0 38390 6.2 1
## 4 1780 8.4 215 7.8 54290 6.2 1
## 5 1760 8.4 210 8.0 28750 6.2 1
## 6 1795 10.0 205 8.2 30490 6.1 1Opis izbrane kategorialne spremenljivke:
fit <- lm(poraba_90 ~ km + pogon,
data = podatki)
summary(fit)##
## Call:
## lm(formula = poraba_90 ~ km + pogon, data = podatki)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.3534 -0.6259 -0.1377 0.5679 5.4287
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.2495515 0.1348049 24.11 <2e-16 ***
## km 0.0161795 0.0008047 20.11 <2e-16 ***
## pogon 0.8746889 0.0714071 12.25 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.098 on 462 degrees of freedom
## Multiple R-squared: 0.6334, Adjusted R-squared: 0.6318
## F-statistic: 399.2 on 2 and 462 DF, p-value: < 2.2e-16podatki$pogonF <- factor(podatki$pogon,
levels = c(1, 2, 3),
labels = c("Pogon spredaj", "Pogon zadaj", "4X4"))
head(podatki)## znamka tip sedezi ccm kw km vrtljajimax navor vrtljajinav Motor dolzina sirina visina medosna teza_kg
## 1 Alfa Romeo 1642,0TS 5 1995 107 146 5800 187 5000 Bencin 455 176 139 266 1380
## 2 Alfa Romeo spyder2,0 2 1969 110 150 6200 187 4000 Bencin 429 178 132 254 1370
## 3 Alfa Romeo 1552,0TS 5 1969 110 150 6200 187 4000 Bencin 444 173 143 254 1300
## 4 Alfa Romeo GTV2,0 2 1969 110 150 6200 187 4000 Bencin 429 178 132 254 1370
## 5 Alfa Romeo 1452 5 1969 110 150 6200 187 4000 Bencin 410 171 143 254 1240
## 6 Alfa Romeo 1551,8TS 5 1747 103 140 6300 165 4000 Bencin 445 173 144 254 1270
## tezadov_kg pospesek hitrost poraba_120 cena poraba_90 pogon pogonF
## 1 1805 9.9 210 8.3 50170 6.5 1 Pogon spredaj
## 2 1630 8.4 210 7.8 56390 6.2 1 Pogon spredaj
## 3 1840 9.0 210 8.0 38390 6.2 1 Pogon spredaj
## 4 1780 8.4 215 7.8 54290 6.2 1 Pogon spredaj
## 5 1760 8.4 210 8.0 28750 6.2 1 Pogon spredaj
## 6 1795 10.0 205 8.2 30490 6.1 1 Pogon spredajfit <- lm(poraba_90 ~ km + pogonF,
data = podatki)
summary(fit)##
## Call:
## lm(formula = poraba_90 ~ km + pogonF, data = podatki)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.5445 -0.5608 -0.1389 0.5362 5.3812
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.9297190 0.1165673 33.712 <2e-16 ***
## km 0.0185355 0.0009052 20.477 <2e-16 ***
## pogonFPogon zadaj 0.1384895 0.1579833 0.877 0.381
## pogonF4X4 1.8758834 0.1410910 13.296 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.068 on 461 degrees of freedom
## Multiple R-squared: 0.6537, Adjusted R-squared: 0.6514
## F-statistic: 290 on 3 and 461 DF, p-value: < 2.2e-16