binomial_pvalue: Calculate p-value for a hypothesis in binomial problem

In mark-andrews/isdsr-pkg: Tools and Datasets to Accompany ISDSR Textbook

Calculate p-value for a hypothesis in binomial problem

Description

Assuming that we have observed a certain number of successes from a binomial distribution, obtain the p-value for a hypothesis about the binomial distribution probability parameter, i.e. the probability of a success on each trial.

Usage

binomial_pvalue(sample_size, observed, hypothesis)

binomial_svalue(sample_size, observed, hypothesis)

binomial_confint(sample_size, observed, level = 0.95)

Arguments

sample_size	The sample size.
observed	The observed number of successes in the sample.
hypothesis	The hypothesized probability parameter.

Functions

• binomial_svalue(): Calculate s-value for a hypothesis in a binomial problem

• binomial_confint(): Calculate confidence interval in a binomial problem

Examples

# p-value for hypothesis that prob=0.4, given 3 successes in 10 trials
binomial_pvalue(10, 3, 0.4)

mark-andrews/isdsr-pkg documentation built on Sept. 13, 2022, 11:47 p.m.