# MATRIKS KORELASI
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.5.3
library(reshape2)
## Warning: package 'reshape2' was built under R version 4.5.3
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
#heatmap
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="brown", mid="blue",midpoint = 0,limit=c(-1,1),name="korelasi")+
theme_minimal()+
labs(tittle="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))
## Ignoring unknown labels:
## • tittle : "Heatmap Dataset mtcars"

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 sedikir 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
#CONSOL 6 DIST. HYPERGEOMETRIK
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