Analisis Deskriptif Dataset MTCARS
Rashieka Cantika Intan
BAB 1 – PENDAHULUAN
Dataset mtcars merupakan dataset klasik berisi 32 mobil dengan 11 variabel performa seperti mpg, hp, wt, cyl, dan am. Analisis ini bertujuan untuk memahami hubungan antara efisiensi bahan bakar (mpg) dan horsepower (hp), serta melihat distribusi variabel utama dalam dataset.
Tujuan penelitian: - Mendeskripsikan struktur dataset. - Menghitung korelasi mpg dan hp. - Membuat visualisasi. - Menganalisis perbedaan mpg berdasarkan transmisi.
BAB 2 – METODE ANALISIS
Dataset diambil langsung dari R:
data(mtcars)
head(mtcars)## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1str(mtcars)## 'data.frame': 32 obs. of 11 variables:
## $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
## $ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
## $ disp: num 160 160 108 258 360 ...
## $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
## $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
## $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
## $ qsec: num 16.5 17 18.6 19.4 17 ...
## $ vs : num 0 0 1 1 0 1 0 1 1 1 ...
## $ am : num 1 1 1 0 0 0 0 0 0 0 ...
## $ gear: num 4 4 4 3 3 3 3 4 4 4 ...
## $ carb: num 4 4 1 1 2 1 4 2 2 4 ...summary(mtcars)## mpg cyl disp hp
## Min. :10.40 Min. :4.000 Min. : 71.1 Min. : 52.0
## 1st Qu.:15.43 1st Qu.:4.000 1st Qu.:120.8 1st Qu.: 96.5
## Median :19.20 Median :6.000 Median :196.3 Median :123.0
## Mean :20.09 Mean :6.188 Mean :230.7 Mean :146.7
## 3rd Qu.:22.80 3rd Qu.:8.000 3rd Qu.:326.0 3rd Qu.:180.0
## Max. :33.90 Max. :8.000 Max. :472.0 Max. :335.0
## drat wt qsec vs
## Min. :2.760 Min. :1.513 Min. :14.50 Min. :0.0000
## 1st Qu.:3.080 1st Qu.:2.581 1st Qu.:16.89 1st Qu.:0.0000
## Median :3.695 Median :3.325 Median :17.71 Median :0.0000
## Mean :3.597 Mean :3.217 Mean :17.85 Mean :0.4375
## 3rd Qu.:3.920 3rd Qu.:3.610 3rd Qu.:18.90 3rd Qu.:1.0000
## Max. :4.930 Max. :5.424 Max. :22.90 Max. :1.0000
## am gear carb
## Min. :0.0000 Min. :3.000 Min. :1.000
## 1st Qu.:0.0000 1st Qu.:3.000 1st Qu.:2.000
## Median :0.0000 Median :4.000 Median :2.000
## Mean :0.4062 Mean :3.688 Mean :2.812
## 3rd Qu.:1.0000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :1.0000 Max. :5.000 Max. :8.000#BAB 3 – HASIL DAN PEMBAHASAN
#3.1 Ringkasan Statistika Deskriptif
summary(mtcars)## mpg cyl disp hp
## Min. :10.40 Min. :4.000 Min. : 71.1 Min. : 52.0
## 1st Qu.:15.43 1st Qu.:4.000 1st Qu.:120.8 1st Qu.: 96.5
## Median :19.20 Median :6.000 Median :196.3 Median :123.0
## Mean :20.09 Mean :6.188 Mean :230.7 Mean :146.7
## 3rd Qu.:22.80 3rd Qu.:8.000 3rd Qu.:326.0 3rd Qu.:180.0
## Max. :33.90 Max. :8.000 Max. :472.0 Max. :335.0
## drat wt qsec vs
## Min. :2.760 Min. :1.513 Min. :14.50 Min. :0.0000
## 1st Qu.:3.080 1st Qu.:2.581 1st Qu.:16.89 1st Qu.:0.0000
## Median :3.695 Median :3.325 Median :17.71 Median :0.0000
## Mean :3.597 Mean :3.217 Mean :17.85 Mean :0.4375
## 3rd Qu.:3.920 3rd Qu.:3.610 3rd Qu.:18.90 3rd Qu.:1.0000
## Max. :4.930 Max. :5.424 Max. :22.90 Max. :1.0000
## am gear carb
## Min. :0.0000 Min. :3.000 Min. :1.000
## 1st Qu.:0.0000 1st Qu.:3.000 1st Qu.:2.000
## Median :0.0000 Median :4.000 Median :2.000
## Mean :0.4062 Mean :3.688 Mean :2.812
## 3rd Qu.:1.0000 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :1.0000 Max. :5.000 Max. :8.000#3.2 Ukuran Pemusatan dan Penyebaran
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionmtcars %>%
summarise(
mpg_mean = mean(mpg),
mpg_median = median(mpg),
mpg_range = max(mpg) - min(mpg),
hp_mean = mean(hp),
hp_median = median(hp),
hp_range = max(hp) - min(hp),
wt_mean = mean(wt),
wt_median = median(wt),
wt_range = max(wt) - min(wt),
am_prop_manual = mean(am) * 100
)## mpg_mean mpg_median mpg_range hp_mean hp_median hp_range wt_mean wt_median
## 1 20.09062 19.2 23.5 146.6875 123 283 3.21725 3.325
## wt_range am_prop_manual
## 1 3.911 40.625#3.3 Visualisasi Data
#a. Histogram mpg
hist(
mtcars$mpg,
main = "Histogram Distribusi Efisiensi Bahan Bakar (mpg)",
xlab = "Miles per Gallon",
col = "lightblue",
border = "black"
)
plot(
mtcars$hp, mtcars$mpg,
xlab = "Horsepower (hp)",
ylab = "Miles per Gallon (mpg)",
main = "Hubungan Horsepower dan MPG",
pch = 19,
col = "darkgreen"
)
abline(lm(mpg ~ hp, data = mtcars), col = "red", lwd = 2)
boxplot(
mpg ~ am,
data = mtcars,
col = c("pink", "lightgreen"),
main = "Boxplot mpg berdasarkan Jenis Transmisi",
xlab = "Transmisi (0 = Otomatis, 1 = Manual)",
ylab = "Miles per Gallon (mpg)"
)
am_table <- table(mtcars$am)
am_prop <- prop.table(am_table) * 100
barplot(
am_prop,
main = "Persentase Jenis Transmisi",
col = c("salmon", "skyblue"),
names.arg = c("Otomatis", "Manual"),
ylab = "Persentase (%)"
)
am_prop##
## 0 1
## 59.375 40.625BAB 4 – KESIMPULAN
Hasil analisis menunjukkan bahwa:
Dataset mtcars memiliki variasi besar pada mpg, hp, dan wt.
Terdapat hubungan negatif kuat antara horsepower dan efisiensi bahan bakar.
Mobil manual memiliki efisiensi bahan bakar lebih baik daripada otomatis.
Visualisasi memperkuat interpretasi statistik.
DAFTAR PUSTAKA
R Core Team (2023). R: A Language and Environment for Statistical Computing.
Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis.
Henderson & Searle (1981). MTCARS Dataset Documentation.