binom.test
Exact Binomial Test

### Description

Performs a hypothesis test to determine if a given sample has a particular proportion parameter.

### Usage

    binom.test(x, n, p = 0.5, alternative = c("two.sided", "less", "greater"),
        conf.level = 0.95)

### Arguments

x | a numeric value that specifies the number of successes or a two-element numeric vector that specifies the number of successes and the number of failures. If you specify a two-element numeric vector, the n argument is ignored and the number of trials is computed by finding the sum of the two elements.
n | a numeric vector that specifies the number of trials. Ignored if argument x is a two-element numeric vector.
p | probability of success to be tested.

alternative | a character string that specifies the alternative hypothesis. To test the hypothesis, type one of the following:
two.sided | to specify that x and p are not equal.
greater | to specify that x is greater than p.
less | to specify that x is less than p.
Note: You only need to enter enough of the character string to create a unique match for the value.
conf.level | a numeric vector in the range [0, 1] that specifies the confidence level for the returned confidence interval.

### Details

The exact probabilities are computed for the binomial distribution.
Value
returns a list with class attribute htest, that represents the result of binomial test:

statistic | number of successes.
parameter | number of trials.
p.value | the p-value.
conf.int | a confidence interval for the true probability of success. The confidence level is recorded in the attribute conf.level.
estimate | the sample estimate of the probability of success calculated by x / n.
null.value | null hypothesis value of the probability of success.
alternative | a character string that returns the alternative hypothesis (two.sided, greater, or less) as specified in the alternative argument.
method | the string Exact binomial test.
data.name | a character vector that describes the data used for the test. The substitute of x or n (not evaluated value) is displayed in data.name.

References
Clopper, C. J. & Pearson, E. S. (1934). "The use of confidence or fiducial limits illustrated in the case of the binomial." Biometrika, 26(4), 404--413.
Conover, W. J. (1980). Practical Nonparametric Statistics, 2nd ed. Wiley, New York.
See Also
Binomial
Examples

    x <- rnorm(100)
    y <- sum(x>0)
    binom.test(y, 100)
    y <- rnorm(100)
    d <- x - y
    binom.test(sum(d>0),length(d))
    binom.test(c(23, 27), alternative = "less", conf.level = 0.90)
    binom.test(23, 23 + 27, alternative = "less", conf.level = 0.90) # the same

Package stats version 6.1.5-18
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