The R Project SVN R

\name{binom.test}
\alias{binom.test}
\title{Exact Binomial Test}
\description{
  Performs an exact test of the null that the probability of success in
  a Bernoulli experiment of length \code{n} is \code{p}, based on the
  number \code{x} of successes observed.
}
\usage{
binom.test(x, n, p = 0.5, alternative = c("two.sided", "less", "greater"),
           conf.level = 0.95)
}
\arguments{
  \item{x}{number of successes.}
  \item{n}{number of trials.}
  \item{p}{probability of success.}
  \item{alternative}{indicates the alternative hypothesis and must be
    one of \code{"two.sided"}, \code{"greater"} or \code{"less"}.
    You can specify just the initial letter.}
  \item{conf.level}{confidence level for the returned confidence
    interval.}
}
\value{
  A list with class \code{"htest"} containing the following components:
  \item{statistic}{the number of successes, \code{x}.}
  \item{parameter}{the number of trials, \code{n}.}
  \item{p.value}{the p-value of the test.}
  \item{conf.int}{a confidence interval for the probability of success.}
  \item{estimate}{the estimated probability of success, \code{x / n}.}
  \item{null.value}{the probability of success under the null,
    \code{p}.}
  \item{alternative}{a character string describing the alternative
    hypothesis.}
  \item{method}{the string \code{"Exact binomial test"}.}
  \item{data.name}{a character string giving the names of the data.}
}
\references{
  Conover, W. J. (1971),
  \emph{Practical nonparametric statistics}.
  New York: John Wiley & Sons.
  Pages 97--104.

  Myles Hollander & Douglas A. Wolfe (1973),
  \emph{Nonparametric statistical inference}.
  New York: John Wiley & Sons.
  Pages 15--22.
}
\seealso{
  \code{\link{prop.test}} for a general (approximate) test for equal or
  given proportions.
}
\examples{
## Conover (1971), p. 97f.
## Under (the assumption of) simple Mendelian inheritance, a cross
##  between plants of two particular genotypes produces progeny 1/4 of
##  which are ``dwarf'' and 3/4 of which are ``giant'', respectively.
##  In an experiment to determine if this assumption is reasonable, a
##  cross results in progeny having 243 dwarf and 682 giant plants.
##  If ``giant'' is taken as success, the null hypothesis is that p =
##  3/4 and the alternative that p != 3/4.
binom.test(682, 682 + 243, p = 3/4)
## => Data are in agreement with the null hypothesis.
}
\keyword{htest}