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How to implement Binomial Distribution in R?

Description

To implement the binomial distribution using R programming.

Process

Four main functions in binomial distribution:

  dbinom(x, size= ,prob=)

   Gives height of the probability distributionat each point pbinom(x, size= ,prob=)

   Gives the cumulative probability ofan event qbinom(p, size= ,prob=)

   It takes the probability value and givesa number whose cumulative value matchesthe probability value.

  rbinom(x, size= ,prob=) Used to generate random numberswhose distribution is binomial.

x -- vector

Size -- Number of success trials

Prob -- Probability of success trails

Sapmle Code

#Binomial Distribution
#dbinom
x<-seq(-10,100,by=1)
y<-dbinom(x,size= 100,prob=0.6)
plot(x,y,col=”blue”)

#pbinom
y<-pbinom(x,size =100,prob=0.3)
plot(x,y,col=”red”)

#qbinom
y<-qbinom(p=0.25,size=100,prob=0.5)
print(y)

#rbinom
x<-rbinom(100,size=100,prob=0.8)
hist(x,col=285)

Screenshots
implement Binomial Distribution in R
Binomial Distribution
Give highest point
Four main functions in binomial  distribution