komstatttttt

y=rpois(n=10,lambda=4)
print(y)

##  [1] 3 2 6 4 3 4 4 2 2 2

set.seed(0123)

z=rbinom(n=10, size=1, prob=7)

## Warning in rbinom(n = 10, size = 1, prob = 7): NAs produced

print(z)

##  [1] NA NA NA NA NA NA NA NA NA NA

library (ggplot2)

## Warning: package 'ggplot2' was built under R version 4.5.3

df <- data.frame(x = rpois(n = 10, lambda = 4))

ggplot(df, aes(x = x)) +
  geom_bar(fill = "black", color = "blue", alpha = 0.8) +
  scale_x_continuous(breaks = min(df$x):max(df$x)) +
  labs(title = "Distribusi Poisson (lambda = 4)",
       x = "Nilai (x)",
       y = "Frekuensi") +
  theme_minimal()

library(ggplot2)

set.seed(123)

# Simulasi distribusi multinomial
hasil <- rmultinom(
  n = 1,
  size = 10,
  prob = c(0.2, 0.3, 0.3, 0.2)
)

df <- data.frame(
  Tingkat_Pendidikan = c("SD", "SMP", "SMA", "Perguruan Tinggi"),
  Frekuensi = as.vector(hasil)
)

# Grafik batang
ggplot(df, aes(x = Tingkat_Pendidikan, 
               y = Frekuensi, 
               fill = Tingkat_Pendidikan)) +
  geom_bar(stat = "identity") +
  scale_fill_manual(
    values = c(
      "SD" = "green",
      "SMP" = "pink",
      "SMA" = "black",
      "Perguruan Tinggi" = "blue"
    )
  ) +
  labs(
    title = "Distribusi Multinomial",
    x = "Tingkat Pendidikan",
    y = "Frekuensi"
  ) +
  theme_minimal()