ztest
              One-sample Z-test.
 h = ztest (x, v) performs a Z-test of the hypothesis
 that the data in the vector x come from a normal distribution with mean
 m, against the alternative that x comes from a normal
 distribution with a different mean m.  The result is h = 0 if the
 null hypothesis ("mean is M") 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, ztest
 performs separate tests along each column of x, and returns a vector of
 results.  For N-D arrays, ztest works along the first non-singleton
 dimension of x.  m and sigma must be a scalars.
 ztest treats NaNs as missing values, and ignores them.
 [h, pval] = ztest (…) 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] = ztest (…) returns a
 100 * (1 - alpha)% confidence interval for the true mean.
 [h, pval, ci, zvalue] = ztest (…)
 returns the value of the test statistic.
 […] = ztest (…, 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" | "mean is not m" (two-tailed, default) | |
| "left" | "mean is less than m" (left-tailed) | |
| "right" | "mean is greater than m" (right-tailed) | 
See also: ttest, vartest, signtest, kstest
Source Code: ztest