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