Student's t-Test
Usage
t.test(x, y = NULL, alternative = "two.sided", mu = 0, paired = FALSE,
var.equal = FALSE, conf.level = 0.95)
Arguments
x
|
a numeric vector of data values.
|
y
|
an optional numeric vector data values.
|
alternative
|
must be one of "two.sided",
"greater" or "less". You can specify just the
initial letter. This parameter indicates the alternative
hypothesis.
|
mu
|
a number indicating the true value of the mean (or
difference in means if you are performing a two sample test).
|
paired
|
a logical indicating whether you want a paired
t-test.
|
var.equal
|
a logical variable indicating whether to treat the
two variances as being equal. If TRUE then the pooled
variance is used to estimate the variance otherwise the Welch
approximation to the degrees of freedom is used.
|
conf.level
|
confidence level of the interval.
|
Description
t.test performs one and two sample t-tests on vectors of data.Details
If paired is TRUE then both x and y must
be specified and they must be the same length. Missing values are
removed (in pairs if paired is TRUE). If
var.equal is TRUE then the pooled estimate of the
variance is used. If var.equal is FALSE then the
variance is estimated separately for both groups and the Welch
modification to the degrees of freedom is used.Value
A list with class "htest" containing the following
components:
statistic
|
the value of the t-statistic.
|
parameters
|
the degrees of freedom for the t-statistic.
|
p.value
|
the p-value for the test.
|
conf.int
|
a confidence interval for the mean appropriate to
the specified alternative hypothesis.
|
estimate
|
the estimated mean or difference in means depending
on whether it was a one-sample test or a two-sample test.
|
null.value
|
the specified hypothesized value of the mean or
mean difference depending on whether it was a one-sample test or
a two-sample test.
|
alternative
|
a character string describing the alternative
hypothesis.
|
method
|
a character string indicating what type of t-test was
performed.
|
data.name
|
a character string giving the name(s) of the data.
|
Examples
t.test(1:10,y=c(7:20)) # P = .00001855
t.test(1:10,y=c(7:20, 200)) # P = .1245 -- NOT significant anymore