# Input data EcoTrack
data_ecotrack <- c(22, 25, 19, 30, 24, 21, 45, 23, 20, 26, 24, 22, 18, 27, 23)
# 1. Mean
mean_val <- mean(data_ecotrack)
print(paste("Mean:", round(mean_val, 2)))
## [1] "Mean: 24.6"
# 2. Median
median_val <- median(data_ecotrack)
print(paste("Median:", median_val))
## [1] "Median: 23"
# 3. Modus menggunakan tabel frekuensi
tabel_frekuensi <- table(data_ecotrack)
modus_val <- names(tabel_frekuensi[tabel_frekuensi == max(tabel_frekuensi)])
print(paste("Modus:", paste(modus_val, collapse = ", ")))
## [1] "Modus: 22, 23, 24"
# Q1 dan Q3 dengan metode yang sesuai rumus manual (type = 6)
q1 <- quantile(data_ecotrack, 0.25, type = 6)
q3 <- quantile(data_ecotrack, 0.75, type = 6)
# IQR
iqr_val <- q3 - q1
# Hasil
print(paste("Q1 (Kuartil Bawah):", q1))
## [1] "Q1 (Kuartil Bawah): 21"
print(paste("Q3 (Kuartil Atas):", q3))
## [1] "Q3 (Kuartil Atas): 26"
print(paste("Interquartile Range (IQR):", iqr_val))
## [1] "Interquartile Range (IQR): 5"
# Varians Sampel
varians_val <- var(data_ecotrack)
# Standar Deviasi Sampel
sd_val <- sd(data_ecotrack)
# Hasil
print(paste("Varians:", round(varians_val, 2)))
## [1] "Varians: 41.54"
print(paste("Standar Deviasi:", round(sd_val, 2)))
## [1] "Standar Deviasi: 6.45"
# Install package jika belum ada
# install.packages("moments")
# Load library
library(moments)
# Menghitung Skewness Momen
skew_val <- skewness(data_ecotrack)
# Hasil
print(paste("Nilai Skewness di R:", round(skew_val, 3)))
## [1] "Nilai Skewness di R: 2.213"