binomial_test: Binomial test

In kim: A Toolkit for Behavioral Scientists

Binomial test

Description

Conduct a binomial test. In other words, test whether an observed proportion of "successes" (e.g., proportion of heads in a series of coin tosses) is greater than the expected proportion (e.g., 0.5). This function uses the 'binom.test' function from the 'stats' package.

Usage

binomial_test(
  x = NULL,
  success = NULL,
  failure = NULL,
  p = 0.5,
  alternative = "two.sided",
  ci = 0.95,
  round_percentages = 0
)

Arguments

x	a vector of values, each of which represents an instance of either a "success" or "failure" (e.g., c("s", "f", "s", "s", "f", "s"))
success	which value(s) indicate "successes"?
failure	(optional) which value(s) indicate "failures"? If no input is provided for this argument, then all the non-NA values that are not declared to be "successes" will be treated as "failures".
p	hypothesized probability of success (default = 0.5)
alternative	indicates the alternative hypothesis and must be one of "two.sided", "greater", or "less". You can specify just the initial letter. By default, alternative = "two.sided"
ci	width of the confidence interval (default = 0.95)
round_percentages	number of decimal places to which to round the percentages in the summary table (default = 0)

Examples

# sample vector
sample_vector <- c(0, 1, 1, 0, 1, 98, 98, 99, NA)
binomial_test(
x = sample_vector,
success = 1, failure = 0)
binomial_test(
x = sample_vector,
success = 1, failure = 0,
p = 0.1,
alternative = "greater")
binomial_test(
x = sample_vector,
success = c(1, 99), failure = c(0, 98),
p = 0.6,
alternative = "less")

kim documentation built on Oct. 9, 2023, 5:08 p.m.