pertemuan 4

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)

## [1] 0.004839414

eks <- function(x,lambda) {lambda*exp((-1)*lambda*x)}
eks(15,0.05)

## [1] 0.02361833

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

## [1] 0.5276334

uniform<-function(x,a=0,b=1){1/(b-a)}
uniform(20,a=10,b=30) #pake di uap

## [1] 0.05

dunif(20,min=10,max=30) #jangan dipake di uap

## [1] 0.05

#postest
#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)

## [1] 0.2419707

#normal biasa ada rata rata(miu) dan standar deviasi (sigma)
#eksponen
1/6

## [1] 0.1666667

eks <- function(x,lambda) {lambda*exp((-1)*lambda*x)}
eks(4,0.1666667)

## [1] 0.08556953

#Untuk P(<=15)
cfdexp<-function(x,lambda=0.1666667) {
  pdf <-function(t) {
    lambda*exp(-lambda*t)
  }
  hasil<-integrate(pdf,lower=0,upper=x)
  return(hasil$value)
}
cfdexp(4,0.1666667)

## [1] 0.4865829

#rata rata atau lamda 1/rata rata, 

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

## [1] 0.125

dunif(6,min=2,max=10) #jangan dipake di uap

## [1] 0.125

#diketahui intervalnya