x: Either a formula or a numeric vector. If formula, it must be of the form ~x indicating the single variable under study. When summary data are provided, x is a numeric vector of success counts.
data: Data frame that supplies the variable x. If not found in data, the variable is searched for in the parent environment.
n: When not empty, this is a numeric vector giving the size of the sample.
p: Specifies Null Hypothesis value for population proportion. If not set, no test is performed.
alternative: "two.sided" requests computation of a two-sided P-value; other possible values are "less" and "greater".
success: When x is a formula, this argument indicates which value of variable x is being counted as a success. When working with formula-data input the value of this parameter MUST be set, even when the variable has only two values.
conf.level: Number between 0 and 1 indicating the confidence-level of the interval supplied.
graph: If TRUE, plot graph of P-value. Ignored if no test is performed.
verbose: Determines whether to return lots of information or only the basics
Returns
an object of class GCbinomtest.
Examples
#Confidence interval only:binomtestGC(~sex,data=m111survey,success="female")#Confidence interval and two-sided test, Null Hypothesis p = 0.5:binomtestGC(~sex,data=m111survey,success="female",p=0.5)#For confidence level other than 95%, use conf.level argument.#For 90% interval:binomtestGC(~sex,data=m111survey,success="female",conf.level=0.90)#For one-sided test, set alternative argument as desired:binomtestGC(~sex,data=m111survey,p=0.50, success="female",alternative="greater")#Summary data:#In one sample, 40 successes in 100 trials. Testing whether p = 0.45.binomtestGC(x=40,n=100,p=0.45)