How to implement normal distribution in R?

Description

To implement the normal distribution using R programming.

Four main functions in normaldistribution:

  dnorm(x, mean= sd= )

   Gives height of the probability distributionat each point for a given mean andstandard deviation.

  pnorm(x, mean= sd= )Gives the probability of a normallydistributed random number to be lessthat the value of a given number.qnorm(p, mean= sd= )

   It takes the probability value and givesa number whose cumulative value matchesthe probability value.rnorm(n, mean= sd= )

   Used to generate random numberswhose distribution is normal.

x -- vector

mean -- Mean value of the sample data.

  It's default value is zero.

prob -- The standard deviation. It'sdefault value is 1.

#Normal Distribution
#dnorm
x<-seq(-10,10,by = 1)
y<-dnorm(x,mean=0,sd=1)
plot(x,y,col=”blue”)

#pnorm
y<-pnorm(x,mean=0,sd=1)
plot(x,y,col=”red”)

#qnorm
x<-seq(0,1,by=0.01)
y<-qnorm(x,mean=0,sd=1)
plot(x,y,col=”green”)

#rnorm
x<-rnorm(100)
hist(x,col=285)

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