#DISTRIBUSI NORMAL#
norm<-function(x,miu,sigma){1/(sigma*sqrt(2*pi))*exp(-1/2*((x-miu)/sigma)^2)}
norm(750,800,50)
## [1] 0.004839414
dnorm(750,mean=800,sd=50) #cara cepat 
## [1] 0.004839414
#Distribusi Eksponensial
#Untuk P(X=15)
eks<-function(x,lambda){lambda*exp((-1)*lambda*x)}
eks(15,0.05)
## [1] 0.02361833
#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(15,0.05)
## [1] 0.5276334

#Distrbusi Uniform uniform<-function (x, a=0,b=1){1/(b-a)} uniform(20,a=10,b=30) dunif(20,min=10,max=30)