Binomial distribution
require('ggplot2')
x <- c(0:10)
y <- dbinom(x, size=10, .5, log = FALSE)
qplot(x, y, color = I("green"),
size = I(2), alpha = I(1/2), geom = c("point"))

the Pascal triangle starts with: x = 0 size = 0 the density = 1 (the vertex of the triangle)
then we are moving to: x = c(0:1) size = 1 //one sample from the choise of two- 0 and 1 the density = 0.5, 0.5 … x = c(0:n) size = n probability = p
The thing that is freequently being forgotten is the way it behaves in asymmetric case, when the probability of a ‘positive’ outcome shifts towards 0 or 1.
y <- dbinom(x, size=10, .75, log = FALSE)
qplot(x, y, color = I("red"),
size = I(2), alpha = I(1/2), geom = c("point"))

and
y <- dbinom(x, size=10, .25, log = FALSE)
qplot(x, y, color = I("magenta"),
size = I(2), alpha = I(1/2), geom = c("point"))

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