binom.test(x,n,p=0.5,alternative=c("two.sided","less","greater"), conf.level=0.95)
Suppose in a coin tossing, the chance to get a head or tail is 50%. In a real case,
we have 100 coin tossings, and get 48 heads, is our original hypothesis true?
> binom.test(48,100)
Exact binomial test data: 48 and 100 number of successes = 48, number of trials = 100, p-value = 0.7644 alternative hypothesis: true probability of success is not equal to 0.5 95 percent confidence interval: 0.3790055 0.5822102 sample estimates: probability of success 0.48
Since the p-value is 0.7644, far greater than 0.05, the hypothesis is accepted.
Let's see another example. Hemophilia A is a genetic disease. If the mother has hemophilia, the possiblity of his male child has hemophilia is 50%.
Suppose the mother has hemophilia only, what is the probability for one boy out of two to be hemophilia?
> dbinom(1, 2, 0.5)[1] 0.5
what is the probability for two boys to be all hemophilia?
> dbinom(2, 2, 0.5)[1] 0.25 > dbinom(0, 2, 0.5)#no hemophilia to all two? [1] 0.25