@stdlib/stats-base-ztest-two-sample-results-float64
v0.0.1
Published
Create a two-sample Z-test double-precision floating-point results object.
Readme
Float64Results
Create a two-sample Z-test double-precision floating-point results object.
Installation
npm install @stdlib/stats-base-ztest-two-sample-results-float64Usage
var Float64Results = require( '@stdlib/stats-base-ztest-two-sample-results-float64' );Float64Results( [arg[, byteOffset[, byteLength]]] )
Returns a two-sample Z-test double-precision floating-point results object.
var results = new Float64Results();
// returns {...}The function supports the following parameters:
- arg: an
ArrayBufferor a data object (optional). - byteOffset: byte offset (optional).
- byteLength: maximum byte length (optional).
A data object argument is an object having one or more of the following properties:
- rejected: boolean indicating whether the null hypothesis was rejected.
- alternative: the alternative hypothesis (e.g.,
'two-sided','less', or'greater'). - alpha: significance level.
- pValue: p-value.
- statistic: test statistic.
- ci: confidence interval as a
Float64Array. - nullValue: difference in means under the null hypothesis.
- xmean: sample mean of
x. - ymean: sample mean of
y.
Float64Results.prototype.rejected
Boolean indicating whether the null hypothesis was rejected.
var results = new Float64Results();
// returns {...}
// ...
var v = results.rejected;
// returns <boolean>Float64Results.prototype.alternative
The alternative hypothesis.
var results = new Float64Results();
// returns {...}
// ...
var v = results.alternative;
// returns <string>Float64Results.prototype.alpha
Significance level.
var results = new Float64Results();
// returns {...}
// ...
var v = results.alpha;
// returns <number>Float64Results.prototype.pValue
The test p-value.
var results = new Float64Results();
// returns {...}
// ...
var v = results.pValue;
// returns <number>Float64Results.prototype.statistic
The test statistic.
var results = new Float64Results();
// returns {...}
// ...
var v = results.statistic;
// returns <number>Float64Results.prototype.ci
Confidence interval.
var results = new Float64Results();
// returns {...}
// ...
var v = results.ci;
// returns <Float64Array>Float64Results.prototype.nullValue
Difference in means under the null hypothesis.
var results = new Float64Results();
// returns {...}
// ...
var v = results.nullValue;
// returns <number>Float64Results.prototype.xmean
Sample mean of x.
var results = new Float64Results();
// returns {...}
// ...
var v = results.xmean;
// returns <number>Float64Results.prototype.ymean
Sample mean of y.
var results = new Float64Results();
// returns {...}
// ...
var v = results.ymean;
// returns <number>Float64Results.prototype.toString( [options] )
Serializes a results object to a formatted string.
var results = new Float64Results();
// returns {...}
// ...
var v = results.toString();
// returns <string>The method supports the following options:
- digits: number of digits to display after decimal points. Default:
4. - decision: boolean indicating whether to show the test decision. Default:
true.
Example output:
Two-sample Z-test
Alternative hypothesis: True difference in means is less than 1.0
pValue: 0.0406
statistic: 9.9901
95% confidence interval: [9.7821, 10.4451]
Test Decision: Reject null in favor of alternative at 5% significance level
Float64Results.prototype.toJSON( [options] )
Serializes a results object as a JSON object.
var results = new Float64Results();
// returns {...}
// ...
var v = results.toJSON();
// returns {...}JSON.stringify() implicitly calls this method when stringifying a results instance.
Float64Results.prototype.toDataView()
Returns a DataView of a results object.
var results = new Float64Results();
// returns {...}
// ...
var v = results.toDataView();
// returns <DataView>Notes
- A results object is a
structproviding a fixed-width composite data structure for storing two-sample Z-test results and providing an ABI-stable data layout for JavaScript-C interoperation.
Examples
var Float64Array = require( '@stdlib/array-float64' );
var Results = require( '@stdlib/stats-base-ztest-two-sample-results-float64' );
var results = new Results({
'rejected': true,
'alpha': 0.05,
'pValue': 0.0132,
'statistic': 2.4773,
'nullValue': 0.0,
'xmean': 3.7561,
'ymean': 3.0129,
'ci': new Float64Array( [ 9.9983, 11.4123 ] ),
'alternative': 'two-sided'
});
var str = results.toString({
'format': 'linear'
});
console.log( str );C APIs
Usage
#include "stdlib/stats/base/ztest/two-sample/results/float64.h"stdlib_stats_ztest_two_sample_float64_results
Structure for holding double-precision floating-point test results.
#include <stdbool.h>
#include <stdint.h>
struct stdlib_stats_ztest_two_sample_float64_results {
// Boolean indicating whether the null hypothesis was rejected:
bool rejected;
// Alternative hypothesis:
int8_t alternative;
// Significance level:
double alpha;
// p-value:
double pValue;
// Test statistic:
double statistic;
// Confidence interval:
double ci[ 2 ];
// Difference in means under the null hypothesis:
double nullValue;
// Sample mean of `x`:
double xmean;
// Sample mean of `y`:
double ymean;
};Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
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License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
