@Rue

2*3; 2/2; 2^2 x=2 x*3;x/x;x^x sqrt(1);exp(2) #creating a vector x<-c(3,1,9) x mean(x);sum(x) x<-c(3,1,9) y<-c(2,5,6)

#rnorm(n, mu,sigma) generates n random values from the normal distribution with mean mu and standard deviation sigma. #If omitted, the parameters default to mu=0 and sigma=1 #pnorm(x,mu,sigma) is the CDF. pnorm(12:16,14,.8) #qnorm(p,mu,sigma) is

#The exponiential distribution models the waiting time between events that occur randomly and independently.\ #Such events are said to occur according to Poisson process. #rexp(n, lamda)generates n random values from the exponiential distribution w

#rhyper(k,N1,N2,n)generates k random values from this hypergeometric distribtion rhyper(10,12,6,4) #dhyper(x,N1,N2,n)returns the probability of drawing x black chiops from a bag that contains N1 black and #N2 white chips when n chips are drawn with

#rpoi(n,lamda)generates n random values from the Poisson distribution. rpois(10,6) #dpois(x,lamda)returns the probability of exactly x occurrences in a single interval. As usual in R, x can be a vector. dpois(0:3,6) #ppois(x,lamda)returns the pr

#rpoi(n,lamda)generates n random values from the Poisson distribution. rpois(10,6) #dpois(x,lamda)returns the probability of exactly x occurrences in a single interval. As usual in R, x can be a vector. dpois(0:3,6) #ppois(x,lamda)returns the pr