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

## Description

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

## Usage

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

## Arguments

 `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

## Value

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

## Author(s)

Frank Schaarschmidt

## References

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

 ```1 2 3 4 5 6``` ```# 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" ) ```