Pemodelan Statistik dan Simulasi

c(5, 3, 18, 5, 9, 32)

## [1]  5  3 18  5  9 32

seq(1, 9, by = 2)

## [1] 1 3 5 7 9

buah <- c("Apel", "Jeruk", "Mangga", "Pisang", "Nanas")

buah_factor <- factor(buah)

table(buah_factor)

## buah_factor
##   Apel  Jeruk Mangga  Nanas Pisang 
##      1      1      1      1      1

list(
  bilangan = c(1, 2, 3),
  huruf = c("x", "y", "z"),
  status = factor(c("Aktif", "Pasif", "Aktif"))
)

## $bilangan
## [1] 1 2 3
## 
## $huruf
## [1] "x" "y" "z"
## 
## $status
## [1] Aktif Pasif Aktif
## Levels: Aktif Pasif

df <- data.frame(
  Nama = c("A", "B", "C", "D"),
  Umur = c(17, 18, 17, 19),
  Status = factor(c("Aktif", "Aktif", "Pasif", "Aktif"))
)
summary(df)

##      Nama                Umur         Status 
##  Length:4           Min.   :17.00   Aktif:3  
##  Class :character   1st Qu.:17.00   Pasif:1  
##  Mode  :character   Median :17.50            
##                     Mean   :17.75            
##                     3rd Qu.:18.25            
##                     Max.   :19.00

array(1:12, dim = c(2, 2, 3))

## , , 1
## 
##      [,1] [,2]
## [1,]    1    3
## [2,]    2    4
## 
## , , 2
## 
##      [,1] [,2]
## [1,]    5    7
## [2,]    6    8
## 
## , , 3
## 
##      [,1] [,2]
## [1,]    9   11
## [2,]   10   12

dim(array(1:12, dim = c(2, 2, 3)))

## [1] 2 2 3

c(1, 2, 3, 4, 5, 6) %% 3 == 0

## [1] FALSE FALSE  TRUE FALSE FALSE  TRUE

length(c(2, 4, 6))

## [1] 3

seq(0, 20, by = 4)

## [1]  0  4  8 12 16 20

rep(c("X", "Y"), 3)

## [1] "X" "Y" "X" "Y" "X" "Y"

gl(3, 2)

## [1] 1 1 2 2 3 3
## Levels: 1 2 3

max(c(1,4,8))        # [1] 8

## [1] 8

min(c(3,5,7))        # [1] 3

## [1] 3

mean(c(5, 10, 5))    # [1] 6.666667

## [1] 6.666667

which(c(0,4,10) > 3)

## [1] 2 3

data <- sample(1:5, 10, replace = TRUE)
hasil <- ifelse(data > 3, "Ya", "Tidak")
hasil

##  [1] "Ya"    "Tidak" "Tidak" "Ya"    "Tidak" "Tidak" "Tidak" "Ya"    "Tidak"
## [10] "Tidak"