Pertemuan ke 7_Komstat

x <- seq(-4, 4, length=100)

y <- dnorm(x, mean=0, sd=1)

plot(x, y, type="l",
     main="Kurva Distribusi Normal",
     xlab="Nilai",
     ylab="Kepadatan")

x <- seq(4, 16, length=100)

y <- dnorm(x, mean=10, sd=2)

plot(x, y, type="l",
     main="Kurva Distribusi Normal (μ = 10, σ = 2)",
     xlab="Nilai",
     ylab="Kepadatan")

# Nilai x
x <- seq(0, 20, length=1000)

# Kurva normal
y1 <- dnorm(x, mean=10, sd=1)
y2 <- dnorm(x, mean=10, sd=2)
y3 <- dnorm(x, mean=10, sd=3)
y4 <- dnorm(x, mean=10, sd=4)

# Grafik pertama
plot(x, y1, type="l",
     main="Kurva Distribusi Normal",
     xlab="Nilai",
     ylab="Kepadatan",
     ylim=c(0, 0.22))

# Menambahkan kurva lainnya
lines(x, y2)
lines(x, y3)
lines(x, y4)

# Garis rata-rata μ = 10
abline(v=10, lty=2)

# Keterangan
legend("topright",
       legend=c("σ = 1", "σ = 2", "σ = 3", "σ = 4"),
       lty=1)

x <- 0:20

y1 <- dnorm(x, mean=10, sd=1)
y2 <- dnorm(x, mean=10, sd=2)
y3 <- dnorm(x, mean=10, sd=3)
y4 <- dnorm(x, mean=10, sd=4)

plot(x, y1, type="o",
     main="Kurva Distribusi Normal",
     xlab="Count",
     ylab="Kepadatan",
     ylim=c(0, 0.22),
     pch=16)

lines(x, y2, type="o", pch=16)
lines(x, y3, type="o", pch=16)
lines(x, y4, type="o", pch=16)

abline(v=10, lty=2)

legend("topright",
       legend=c("σ=1", "σ=2", "σ=3", "σ=4"),
       lty=1,
       pch=16)

# Parameter distribusi
mu <- c(0, 2, 5, 10, 15)
sigma <- c(1, 1, 5, 3, 0.1)

# Warna masing-masing kurva
warna <- c("blue", "red", "green", "purple", "orange")

# Membuat nilai X (Count)
x <- seq(-5, 20, length=1000)

# Membuat kurva normal
y1 <- dnorm(x, mean=mu[1], sd=sigma[1])
y2 <- dnorm(x, mean=mu[2], sd=sigma[2])
y3 <- dnorm(x, mean=mu[3], sd=sigma[3])
y4 <- dnorm(x, mean=mu[4], sd=sigma[4])
y5 <- dnorm(x, mean=mu[5], sd=sigma[5])

# Grafik kurva pertama
plot(x, y1,
     type="l",
     col=warna[1],
     lwd=2,
     ylim=c(0, 0.45),
     main="Simulasi Distribusi Normal (5 Variabel)",
     xlab="Count (X)",
     ylab="Kepadatan")

# Menambahkan 4 kurva lainnya
lines(x, y2, col=warna[2], lwd=2)
lines(x, y3, col=warna[3], lwd=2)
lines(x, y4, col=warna[4], lwd=2)
lines(x, y5, col=warna[5], lwd=2)

# Garis rata-rata μ = 10
abline(v=10, lty=2)

# Legenda
legend("topright",
       legend=c(
         "Kurva 1: μ=0, σ=1",
         "Kurva 2: μ=2, σ=1",
         "Kurva 3: μ=5, σ=5",
         "Kurva 4: μ=10, σ=3",
         "Kurva 5: μ=15, σ=0.1"
       ),
       col=warna,
       lwd=2)

# Membagi tampilan menjadi 3 x 3 grafik
par(mfrow=c(3,3))

# 1. DISTRIBUSI NORMAL
x <- seq(0,20,length=1000)
y <- dnorm(x, mean=10, sd=2)

plot(x,y,type="l",col="blue",lwd=2,
     main="Distribusi Normal",
     xlab="X",ylab="Kepadatan")


# 2. DISTRIBUSI t
x <- seq(-5,5,length=1000)
y <- dt(x,df=5)

plot(x,y,type="l",col="red",lwd=2,
     main="Distribusi t",
     xlab="X",ylab="Kepadatan")


# 3. DISTRIBUSI F
x <- seq(0,6,length=1000)
y <- df(x,df1=5,df2=10)

plot(x,y,type="l",col="green",lwd=2,
     main="Distribusi F",
     xlab="X",ylab="Kepadatan")


# 4. DISTRIBUSI CHI-SQUARE
x <- seq(0,20,length=1000)
y <- dchisq(x,df=5)

plot(x,y,type="l",col="purple",lwd=2,
     main="Distribusi Chi-Square",
     xlab="X",ylab="Kepadatan")


# 5. DISTRIBUSI GAMMA
x <- seq(0,10,length=1000)
y <- dgamma(x,shape=2,rate=1)

plot(x,y,type="l",col="orange",lwd=2,
     main="Distribusi Gamma",
     xlab="X",ylab="Kepadatan")


# 6. DISTRIBUSI WEIBULL
x <- seq(0,8,length=1000)
y <- dweibull(x,shape=2,scale=2)

plot(x,y,type="l",col="brown",lwd=2,
     main="Distribusi Weibull",
     xlab="X",ylab="Kepadatan")


# 7. DISTRIBUSI EKSPONENSIAL
x <- seq(0,8,length=1000)
y <- dexp(x,rate=1)

plot(x,y,type="l",col="pink",lwd=2,
     main="Distribusi Eksponensial",
     xlab="X",ylab="Kepadatan")


# 8. DISTRIBUSI PARETO
# R tidak memiliki fungsi dpareto bawaan,
# sehingga rumus kepadatannya dibuat manual

x <- seq(1,10,length=1000)

shape <- 3
scale <- 1

y <- shape*scale^shape/x^(shape+1)

plot(x,y,type="l",col="darkgreen",lwd=2,
     main="Distribusi Pareto",
     xlab="X",ylab="Kepadatan")


# 9. DISTRIBUSI UNIFORM
x <- seq(0,10,length=1000)
y <- dunif(x,min=0,max=10)

plot(x,y,type="l",col="darkblue",lwd=2,
     main="Distribusi Uniform",
     xlab="X",ylab="Kepadatan")

# Mengembalikan tampilan menjadi 1 grafik
par(mfrow=c(1,1))