t.test {base} | R Documentation |
t.test performs one and two sample t-tests on vectors of data.
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.
t.test(x, y = NULL, alternative = "two.sided", mu = 0, paired = FALSE,
var.equal = FALSE, conf.level = 0.95)
x |
a numeric vector of data values. |
y |
an optional numeric vector data values. |
alternative |
must be one of |
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 |
conf.level |
confidence level of the interval. |
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. |