Data Ecotrack_3337260014

# TUGAS PENDALAMAN MATERI - ECOTRACK


# 1. MEMASUKKAN DATA
data <- c(22, 25, 19, 30, 24, 21, 45, 23, 20, 26, 24, 22, 18, 27, 23)

# Melihat data
data

##  [1] 22 25 19 30 24 21 45 23 20 26 24 22 18 27 23

# Mean
mean(data)

## [1] 24.6

# Median
median(data)

## [1] 23

# Modus
modus <- function(x) {
  frekuensi <- table(x)
  modus <- names(frekuensi[frekuensi == max(frekuensi)])
  as.numeric(modus)
}

modus(data)

## [1] 22 23 24

# 3. Q1, Q3, DAN IQR


# Kuartil
quantile(data, probs = c(0.25, 0.75))

##  25%  75% 
## 21.5 25.5

# Q1
Q1 <- quantile(data, 0.25)

# Q3
Q3 <- quantile(data, 0.75)

# IQR
IQR(data)

## [1] 4

Q1

##  25% 
## 21.5

Q3

##  75% 
## 25.5

IQR(data)

## [1] 4

# 4. VARIANS DAN STANDAR DEVIASI


# Varians sampel
var(data)

## [1] 41.54286

# Standar deviasi sampel
sd(data)

## [1] 6.445375

# Varians populasi (tambahan)
var_populasi <- sum((data - mean(data))^2) / length(data)
var_populasi

## [1] 38.77333

# Standar deviasi populasi
sd_populasi <- sqrt(var_populasi)
sd_populasi

## [1] 6.226824

# 5. SKEWNESS PEARSON


# Koefisien skewness Pearson
skewness_pearson <- 3 * (mean(data) - median(data)) / sd(data)

skewness_pearson

## [1] 0.7447201

# 6. VERIFIKASI SKEWNESS DENGAN R



library(e1071)

# Skewness
skewness(data)

## [1] 1.995046

# 7. RINGKASAN SEMUA HASIL

cat("Mean       :", mean(data), "\n")

## Mean       : 24.6

cat("Median     :", median(data), "\n")

## Median     : 23

cat("Modus      :", modus(data), "\n")

## Modus      : 22 23 24

cat("Q1         :", Q1, "\n")

## Q1         : 21.5

cat("Q3         :", Q3, "\n")

## Q3         : 25.5

cat("IQR        :", IQR(data), "\n")

## IQR        : 4

cat("Varians    :", var(data), "\n")

## Varians    : 41.54286

cat("SD         :", sd(data), "\n")

## SD         : 6.445375

cat("Skewness Pearson :", skewness_pearson, "\n")

## Skewness Pearson : 0.7447201

cat("Skewness e1071   :", skewness(data), "\n")

## Skewness e1071   : 1.995046