Description Usage Arguments Value Author(s) Examples

Wrapper for binom.test in package `stats`

. Employs the binomial distribution
in inferential procedures for a single proportion.

1 2 3 | ```
binomtestGC(x,data=parent.frame(),n=numeric(),p=NULL,
alternative=c("two.sided","less","greater"),
success="yes",conf.level=0.95,graph=FALSE,verbose=TRUE)
``` |

`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 |

an object of class GCbinomtest.

Homer White hwhite0@georgetowncollege.edu

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
#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)
``` |

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