### Function Reference: `vartest2`

statistics: h = vartest2 (x, y)
statistics: h = vartest2 (x, y, name, value)
statistics: [h, pval] = vartest2 (…)
statistics: [h, pval, ci] = vartest2 (…)
statistics: [h, pval, ci, stats] = vartest2 (…)

Two-sample F test for equal variances.

`h = vartest2 (x, y)` performs an F test of the hypothesis that the independent data in vectors x and y come from normal distributions with equal variance, against the alternative that they come from normal distributions with different variances. The result is h = 0 if the null hypothesis ("variance are equal") cannot be rejected at the 5% significance level, or h = 1 if the null hypothesis can be rejected at the 5% level.

x and y may also be matrices or N-D arrays. For matrices, `vartest2` performs separate tests along each column and returns a vector of results. For N-D arrays, `vartest2` works along the first non-singleton dimension and x and y must have the same size along all the remaining dimensions.

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

`[h, pval] = vartest (…)` returns the p-value. That is the probability of observing the given result, or one more extreme, by chance if the null hypothesisis true.

`[h, pval, ci] = vartest (…)` returns a 100× (1 - alpha)% confidence interval for the true ratio var(X)/var(Y).

`[h, pval, ci, stats] = vartest (…)` returns a structure with the following fields:

| `fstat` | the value of the test statistic
| `df1` | the numerator degrees of freedom of the test
| `df2` | the denominator degrees of freedom of the test

`[…] = vartest (…, name, value), …` specifies one or more of the following name/value pairs:

| Name | Value
--- | --- | ---
| `"alpha"` | the significance level. Default is 0.05.
| `"dim"` | dimension to work along a matrix or an N-D array.
| `"tail"` | a string specifying the alternative hypothesis

| `"both"` | variance is not v (two-tailed, default)
| `"left"` | variance is less than v (left-tailed)
| `"right"` | variance is greater than v (right-tailed)

See also: ttest2, kstest2, bartlett_test, levene_test

Source Code: vartest2