### Function Reference: `ttest2`

statistics: [h, pval, ci, stats] = ttest2 (x, y)
statistics: [h, pval, ci, stats] = ttest2 (x, y, Name, Value)

Perform a t-test to compare the means of two groups of data under the null hypothesis that the groups are drawn from distributions with the same mean.

x and y can be vectors or matrices. For matrices, `ttest2` performs separate t-tests along each column, and returns a vector of results. x and y must have the same number of columns. The Type I error rate of the resulting vector of pval can be controlled by entering pval as input to the function `multcompare`.

`ttest2` treats NaNs as missing values, and ignores them.

For a nested t-test, use `anova2`.

The argument `"alpha"` can be used to specify the significance level of the test (the default value is 0.05). The string argument `"tail"`, can be used to select the desired alternative hypotheses. If `"tail"` is `"both"` (default) the null is tested against the two-sided alternative `mean (x) != m`. If `"tail"` is `"right"` the one-sided alternative `mean (x) > m` is considered. Similarly for `"left"`, the one-sided alternative `mean (x) < m` is considered.

When `"vartype"` is `"equal"` the variances are assumed to be equal (this is the default). When `"vartype"` is `"unequal"` the variances are not assumed equal.

When argument x and y are matrices the `"dim"` argument can be used to select the dimension over which to perform the test. (The default is the first non-singleton dimension.)

If h is 0 the null hypothesis is accepted, if it is 1 the null hypothesis is rejected. The p-value of the test is returned in pval. A 100(1-alpha)% confidence interval is returned in ci. stats is a structure containing the value of the test statistic (tstat), the degrees of freedom (df) and the sample standard deviation (sd).

See also: hotelling_ttest2, anova1, hotelling_ttest, ttest

Source Code: ttest2