Simulasi Sederhana: Variabel Random Uniform

#Simulasi 1000 variabel random dari distribusi uniform
set.seed(123) #set seed untuk reproducibility
n <- 1000
uniform_data <- runif(n, min = 0, max = 1)

#Plot histogram
hist(uniform_data, breaks = 30, main = "Histogram Distribusi Uniform", xlab = "Nilai", col = "blue")

Simulasi Distribusi Diskrit: Distribusi Binomial

#Simulasi 1000 variabel random dari diatribusi binomial
n_trials <- 10 #jumlah Percobaan
p_succcess <- 0.5 #Probabilitas sukses
binomial_data <- rbinom(n, size = n_trials, prob = p_succcess)

#Plot histogram
hist(binomial_data, breaks = 30, main = "Histogram Distribusi Binomial", xlab = "Jumlah Sukses", col = "blue")

Simulasi Distribusi Kontinu: Distribusi Normal

#Simulasi 1000 variabel random dari distribusi normal
mu <- 0 #Mean
sigma <- 1 #Standar deviasi
normal_data <- rnorm(n, mean = mu, sd = sigma)

#Plot Histogram
hist(normal_data, breaks = 30, main = "Histogram Distribusi Normal", xlab = "Nilai", col = "blue")

Distribusi Poisson (Diskrit)

lambda <- 3 # Parameter lambda
poisson_data <- rpois(n, lambda)
hist(poisson_data, breaks = 30, main = "Histogram Distribusi POisson", xlab = " Jumlah Kejadian", col = "blue")

Distribusi Eksponensial (Kontinu)

rate <- 1 # Parameter rate
exp_data <- rexp(n, rate)
hist(exp_data, breaks = 30, main = "Histogram Distribusi Eksponensial", xlab = "Nilai", col = "blue")