vartest - Chi-square variance test

Syntax

H = vartest(X,V) H = vartest(X,V,alpha) H = vartest(X,V,alpha,tail) [H,P] = vartest(...) [H,P,CI] = vartest(...) [H,P,CI,STATS] = vartest(...) [...] = vartest(X,V,alpha,tail,dim)

Description

H = vartest(X,V) performs a chi-square test of the hypothesis that the data in the vector X comes 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-dimensional array. For matrices, vartest performs separate tests along each column of X, and returns a row vector of results. For n-dimensional arrays, vartest works along the first nonsingleton dimension of X. V must be a scalar.

H = vartest(X,V,alpha) performs the test at the significance level (100*alpha)%. alpha has a default value of 0.05 and must be a scalar.

H = vartest(X,V,alpha,tail) performs the test against the alternative hypothesis specified by tail, where tail is a single string from the following choices:

'both' — Variance is not V (two-tailed test). This is the default.
'right' — Variance is greater than V (right-tailed test).
'left' — Variance is less than V (left-tailed test).

[H,P] = vartest(...) returns the p-value, i.e., the probability of observing the given result, or one more extreme, by chance if the null hypothesis is true. Small values of P cast doubt on the validity of the null hypothesis.

[H,P,CI] = vartest(...) returns a 100*(1-alpha)% confidence interval for the true variance.

[H,P,CI,STATS] = vartest(...) returns the structure STATS with the following fields: