PrakKomstat_Pert3

library(ggplot2)
library(reshape2)
data<-datasets::mtcars
data_mtcars<-data[, c("mpg", "disp", "hp", "wt", "qsec")]

#Matriks korelasi
cor_mtcars<-cor(data_mtcars)
cor_mtcars

##             mpg       disp         hp         wt       qsec
## mpg   1.0000000 -0.8475514 -0.7761684 -0.8676594  0.4186840
## disp -0.8475514  1.0000000  0.7909486  0.8879799 -0.4336979
## hp   -0.7761684  0.7909486  1.0000000  0.6587479 -0.7082234
## wt   -0.8676594  0.8879799  0.6587479  1.0000000 -0.1747159
## qsec  0.4186840 -0.4336979 -0.7082234 -0.1747159  1.0000000

#eatmap
data_cor<-melt(cor_mtcars)
ggplot(data_cor, aes(Var1, Var2, fill = value))+
  geom_tile(color="black")+
  geom_text(aes(label=round(value, 2)), color="black")+
  scale_fill_gradient2(low="red",high="green", mid="yellow",
                       midpoint=0, limit=c(-1,1), name="Korelasi")+
  theme_minimal()+
  labs(title="Heatmap Dataset mtcars",
       x="variabel 1", y="Variabel 2")+
  theme(plot.title=element_text(hjust=0.5),
        axis.text.x=element_text(hjust=0.5))

bern<-function(x,p){p^x*(1-p)^(1-x)}
bern(1,3/6)

## [1] 0.5

cmfbinom<-function(k,n,p){
  #Validasi Input
  if(k<0 || n < 0 || p < 0 || p > 1 ){
    stop("Input Tidak Valid")
  }
  #inisialisasi CMF
  cmf<-0
  #Menghitung CMF
  for (x in 0:k){
    prob<-choose(n,x)*(p^x)*((1-p)^(n-x))
    cmf<-cmf+prob
  }
  return(cmf)
}
#Peluang paling sedikit 2 orang sembuh = 1- P(X<= 1)
Peluang = 1 - cmfbinom(1 ,12 ,0.2)
Peluang

## [1] 0.7251221

cmfpois<-function(x, lambda){
  if (lambda<=0){
    stop("Lambda Harus Bernilai > 0")
  }
  if (x<0){
    return(0)
  }
  cmf<-0
  for(k in 0:x){
    cmf<-cmf+(exp(-lambda)*(lambda^k)/ factorial(k))
  }
  return(cmf)
}
Peluang2<-cmfpois(10,2)-cmfpois(0,2)
Peluang2

## [1] 0.8646564

geo<-function(x,p){p*(1-p)^(x-1)}
geo(5,0.3)

## [1] 0.07203

hyper<-function(x,N,n,k){(((factorial(k)/(factorial(k-x)*factorial(x)))*(factorial(N-k)/((factorial((N-k)-(n-x)))*(factorial(n-x)))))/(factorial(N)/(factorial(N-n)*factorial(n))))}
hyper(2,100,10,5)

## [1] 0.07021881