#dnorm(x) returns the height of the probability distribution at each point x. 
 dnorm(0)            #1/sqrt(2*pi)
 dnorm(0)*sqrt(2*pi)
 dnorm(0,mean=4,sd=10)
 x <- seq(-5,5,by=.01)
 y <- dnorm(x) 
 plot(x,y)
 plot(x,y,type="l")
 y <- dnorm(x,mean=2.5,sd=.5) 
 plot(x,y,type="l")
 
#pnorm(x) returns the P(X<=x) for a Normal RV - the Cumulative Distribution Function (CDF)
 pnorm(0)
 pnorm(1.96)

#qnorm(x) returns the xth quantile for a Normal distribution (the inverse of pnorm)
 qnorm(.025)
 qnorm(.975)
 
#rnorm(n) returns n random deviates from a normal distribution
 y <- rnorm(200,mean=-2,sd=4)
 hist(y)
 
#Binomial Distribution
 x <- seq(0,20,by=1)
 y <- dbinom(x,20,0.2); names(y) <- x
 barplot(y)
 
 y <- dbinom(x,20,0.6); names(y) <- x
 barplot(y)
 
 pbinom( 8,20,0.6)
 pbinom(12,20,0.6)

 qbinom(0.6,20,1/2)
 
#---------------------------------------------
#cor(x,y) correlation between variables x & y
 x <- rnorm(500)
 y <- 3*(x+rnorm(500,sd=2))
 plot(x,y)
 cor(x,y)
 
 y <- 3*(x+rnorm(500,sd=1))
 plot(x,y)
 cor(x,y)

http://www.cyclismo.org/tutorial/R/