Z-Test

One-sample z-Test.

Usage

var ztest = require( '@stdlib/math/stats/ztest' );

ztest( x, sigma[, opts] )

The function performs a one-sample z-test for the null hypothesis that the data in array or typed array x is drawn from a normal distribution with mean zero and known standard deviation sigma.

var normal = require( '@stdlib/random/base/normal' ).factory;

var rnorm = normal( 0.0, 2.0, {
    'seed': 5776
});

var arr = new Array( 300 );
var i;
for ( i = 0; i < arr.length; i++ ) {
    arr[ i ] = rnorm();
}

var out = ztest( arr, 2.0 );
/* e.g., returns
    {
        rejected: false,
        pValue: ~0.155,
        statistic: -1.422,
        ci: [~-0.391,~0.062],
        // ...
    }
*/

The returned object comes with a .print() method which when invoked will print a formatted output of the hypothesis test results. print accepts a numdigits option that controls the number of decimal digits displayed for the outputs.

var table = out.print({
    'numdigits': 3
});
console.log( table );
/* e.g., =>
    One-sample z-test

    Alternative hypothesis: True mean is not equal to 0

        pValue: 0.155
        statistic: -1.422
        95% confidence interval: [-0.391,0.062]

    Test Decision: Fail to reject null in favor of alternative at 5% significance level
*/

The ztest function accepts the following options:

  • alpha: number in the interval [0,1] giving the significance level of the hypothesis test. Default: 0.05.
  • alternative: Either two-sided, less or greater. Indicates whether the alternative hypothesis is that the mean of x is larger than mu (greater), smaller than mu (less) or equal to mu (two-sided). Default: two-sided.
  • mu: number denoting the hypothesized true mean under the null hypothesis. Default: 0.

By default, the hypothesis test is carried out at a significance level of 0.05. To choose a different significance level, set the alpha option.

var table;
var out;
var arr;

arr = [ 2, 4, 3, 1, 0 ];

out = ztest( arr, 2.0, {
    'alpha': 0.01
});
table = out.print();
/* e.g., returns
    One-sample z-test

    Alternative hypothesis: True mean is not equal to 0

        pValue: 0.0253
        statistic: 2.2361
        99% confidence interval: [-0.3039,4.3039]

    Test Decision: Fail to reject null in favor of alternative at 1% significance level
*/

out = ztest( arr, 2.0, {
    'alpha': 0.1
});
table = out.print();
/* e.g., returns
    One-sample z-test

    Alternative hypothesis: True mean is not equal to 0

        pValue: 0.0253
        statistic: 2.2361
        90% confidence interval: [0.5288,3.4712]

    Test Decision: Reject null in favor of alternative at 10% significance level
*/

To test whether the data comes from a distribution with a mean different than zero, set the mu option.

var out;
var arr;

arr = [ 4, 4, 6, 6, 5 ];

out = ztest( arr, 1.0, {
    'mu': 5.0
});
/* e.g., returns
    {
        rejected: false,
        pValue: 1,
        statistic: 0,
        ci: [ ~4.123, ~5.877 ],
        // ...
    }
*/

By default, a two-sided test is performed. To perform either of the one-sided tests, set the alternative option to less or greater.

var table;
var out;
var arr;

arr = [ 4, 4, 6, 6, 5 ];

out = ztest( arr, 1.0, {
    'alternative': 'less'
});
table = out.print();
/* e.g., returns
    One-sample z-test

    Alternative hypothesis: True mean is less than 0

        pValue: 1
        statistic: 11.1803
        95% confidence interval: [-Infinity,5.7356]

    Test Decision: Fail to reject null in favor of alternative at 5% significance level
*/

out = ztest( arr, 1.0, {
    'alternative': 'greater'
});
table = out.print();
/* e.g., returns
    One-sample z-test

    Alternative hypothesis: True mean is greater than 0

        pValue: 0
        statistic: 11.1803
        95% confidence interval: [4.2644,Infinity]

    Test Decision: Reject null in favor of alternative at 5% significance level
*/

Examples

var normal = require( '@stdlib/random/base/normal' ).factory;
var ztest = require( '@stdlib/math/stats/ztest' );

var rnorm;
var arr;
var out;
var i;

rnorm = normal( 5.0, 4.0, {
    'seed': 37827
});
arr = new Array( 500 );
for ( i = 0; i < arr.length; i++ ) {
    arr[ i ] = rnorm();
}

// Test whether true mean is equal to zero:
out = ztest( arr, 4.0 );
console.log( out.print() );
/* e.g., =>
    One-sample z-test

    Alternative hypothesis: True mean is not equal to 0

        pValue: 0
        statistic: 28.6754
        95% confidence interval: [4.779,5.4802]

    Test Decision: Reject null in favor of alternative at 5% significance level
*/

// Test whether true mean is equal to five:
out = ztest( arr, 4.0, {
    'mu': 5.0
});
console.log( out.print() );
/* e.g., =>
    One-sample z-test

    Alternative hypothesis: True mean is not equal to 5

        pValue: 0.4688
        statistic: 0.7245
        95% confidence interval: [4.779,5.4802]

    Test Decision: Fail to reject null in favor of alternative at 5% significance level
*/