# BinomialDistibution.R
# Calculating binomial probabilities is easy in R. The function 'binom.test' takes in
# three variables: (1) K, the number of sucessful oucomes, (2) N, the total number of trials,
# and (3) P, the probability of a succesful outcome on any given trial.
#
# A fourth argument can be 'alternative = "less"', or 'alternative = "greater"', depending on
# whether you want Pr(xk)
# Example: Given 10 flips of a fair 50/50 coin, what is the probability of obtaining 6 or more heads?
out <- binom.test(6,10,.5,
alternative = "greater")
# The result can be found in the field 'p.value':
print(out$p.value)
# Example: If you guess on a 20 question multiple choice test where each question has 5 possible
# answers, what is the probability of getting 4 or less correct?
out <- binom.test(4,20,1/5,
alternative = "less")
print(out$p.value)
# Example: If a basketball player has a 2 out 3 chance of making a free throw on any given try,
# and all tries are independent, what is the probability of making 7 or more out of 10?
out <- binom.test(7,10,2/3,
alternative = "greater")
print(out$p.value)