binTest: Hypothesis tests for One Binomial Proportion
In binGroup: Evaluation and Experimental Design for Binomial Group Testing

Description Usage Arguments Value Author(s) References See Also Examples

Calculates p-values for hypothesis tests of a single binomial proportion.

1 2	binTest(n, y, p.hyp, alternative = "two.sided", method = "Exact")

`n`	single integer value, number of trials (number of individuals under observation)
`y`	single integer value, number of successes (number of individuals showing the trait of interest)
`p.hyp`	single numeric value between 0 and 1, specifying the hypothetical threshold proportion to test against
`alternative`	character string defining the alternative hypothesis, either 'two.sided', 'less' or 'greater'
`method`	character string defining the test method to be used: can be one of `"Exact"` for an exact test corresponding to the Clopper-Pearson confidence interval, uses `binom.test(stats)` `"Score"` for a Score test, corresponding to the Wilson confidence interval `"Wald"` for a Wald test corresponding to the Wald confidence interval

A list containing:

`p.value`	the p value of the test
`estimate`	the estimated proportion
`p.hyp`	as input
`alternative`	as input
`method`	as input

Frank Schaarschmidt

Santner, T.J. and Duffy, D.E. (1989) The statistical analysis of discrete data. Springer Verlag New York Berlin Heidelberg. Chapter 2.1.

binom.test(stats) for the exact test and corresponding confindence interval

# 200 seeds are taken from a seed lot.
# 2 are found to be defective.
# H0: p >= 0.02  shall be rejected in favor of  HA: p < 0.02.
# The exact test shall be used for decision:

binTest(n=200, y=2, p.hyp=0.02, alternative="less", method="Exact" )