vartest
              One-sample test of variance.
 h = vartest (x, v) performs a chi-square test of the
 hypothesis that the data in the vector x come from a normal
 distribution with variance v, against the alternative that x
 comes from a normal distribution with a different variance.  The result is
 h = 0 if the null hypothesis ("variance is V") cannot be rejected at
 the 5% significance level, or h = 1 if the null hypothesis can be
 rejected at the 5% level.
 x may also be a matrix or an N-D array.  For matrices, vartest
 performs separate tests along each column of x, and returns a vector of
 results.  For N-D arrays, vartest works along the first non-singleton
 dimension of x.  v must be a scalar.
 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 variance.
 [h, pval, ci, stats] = vartest (…)
 returns a structure with the following fields:
| chisqstat | the value of the test statistic | |
| df | the 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: ttest, ztest, kstest
Source Code: vartest