POST TEST 1

#DISTRIBUSI NORMAL#
norm<-function(x,miu,sigma){1/(sigma*sqrt(2*pi))*exp(-1/2*((x-miu)/sigma)^2)}
norm(4,5,1)

## [1] 0.2419707

dnorm(4,mean=5,sd=1) #cara cepat 

## [1] 0.2419707

#Distribusi Eksponensial
#Untuk P(X=15)
eks<-function(x,lambda){lambda*exp((-1)*lambda*x)}
eks(4,0.167)

## [1] 0.08562641

#Untuk P(X<15)
cdfexp <- function(x, lambda = 0.05) {
  pdf <- function(t) {
    lambda * exp(-lambda * t)
  }
  hasil<- integrate(pdf, lower = 0, upper = x)
  return(hasil$value)
}
cdfexp(4,0.167)

## [1] 0.487267

#Distribusi Uniform
uniform<-function(x,a=0,b=1){1/(b-a)}
uniform(6,a=2,b=10)

## [1] 0.125

dunif(6,min=2,max=10)

## [1] 0.125