ttestGC: t-Procedures
In tigerstats: R Functions for Elementary Statistics

Description Usage Arguments Value Author(s) Examples

t-tests and confidence intervals for one and two samples.

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ttestGC(x=NULL,data=parent.frame(),mean=numeric(),sd=numeric(),n=numeric(),
 mu=NULL,alternative=c("two.sided","less","greater"),var.equal=FALSE,
 conf.level=0.95,graph=FALSE,first=NULL,verbose=TRUE)

`x`	If not NULL, then must be a formula. If a formula, then data must be a dataframe. For one sample t-procedures, x is of the form ~var. For two-sample procedures, x is of the form resp~exp, where exp is factor with two values. If x is of form ~var1-var2, then matched pairs procedures are performed.
`data`	A data frame containing variables in formula x. If some variables are not in data, then they are searched for in the parent environment.
`mean`	When not NULL, contains sample mean(s). Length 1 for one sample t-procedures, Length 2 for two-sample procedures.
`sd`	When not NULL, contains sample standard deviation(s).
`n`	When not NULL, contains sample size(s).
`mu`	Contains the null value for the parameter of interest. 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".
`var.equal`	When FALSE, use Welch's approximation to the degrees of freedom.
`conf.level`	Number between 0 and 1 indicating the confidence-level of the interval supplied.
`graph`	If TRUE, plot graph of P-value.
`first`	If assigned, gives the value of the explanatory variable that is to count as the first sample.
`verbose`	Indicate how much output goes to console

A list of class "GCttest" Components of the list that may be usefully queried include: "statistic", "p.value", and "interval".

Homer White hwhite0@georgetowncollege.edu for matched pairs.

#One-sample t, 95%-confidence interval only:
ttestGC(~fastest,data=m111survey)

#For other confidence levels, set argument conf.level as desired.  For 90%-interval:
ttestGC(~fastest,data=m111survey,conf.level=0.90)

# One-sample t, 95%-confidence interval and two-sided test with H_0:  mu = 100:
ttestGC(~fastest,data=m111survey,mu=100)

#Two-sample t, 95%-confidence interval only:
ttestGC(fastest~sex,data=m111survey)

#control order of groups with argument first:
ttestGC(fastest~sex,data=m111survey,first="male")

# Matched pairs, confidence interval with one-sided test, H_0: mu-d = 0:
ttestGC(~ideal_ht-height,data=m111survey,mu=0,alternative="greater")

#Summary data, one sample, one-sided test with H_0:  mu = 52.5:
ttestGC(mean=55,sd=4,n=16,mu=52.5,alternative="greater")

#Summary data, two samples:
ttestGC(mean=c(50,55),sd=c(3,4),n=c(25,40),mu=0)