twoSampleTTest()
The two-sample t-test is a method used to test whether the unknown population means of two groups are equal or not. It helps to answer questions like “whether the average success rate is higher after implementing a new sales tool than before” or “whether the test results of patients who received a drug are better than test results of those who received a placebo”.
Therefore this method is wided used to analysze the result in A/B test. You can use this test when the values of data are independent and randomly sampled from two normal distributions.
Import
import * as datacook from '@pipcook/datacook';
const { twoSampleTTest } = datacook.Model;
Syntax
twoSampleTTest(samples1: number[], samples2: number[]): TwoSampleTTestResult
Parameters
| Parameter | type | description |
|---|---|---|
| samples1 | number[] | first sample data values |
| samples2 | number[] | second sample data values |
Returns
test result with following structure:
{
t: number, /* t value for statistical test */
pValue: number, /* p value */
df: number, /* degrees of freedom */
mean1: number, /* mean for first sample input */
mean2: number, /* mean for second sample input */
confidenceInterval: number, /* 95% confidence interval for x - y */
}
Usage
const x = [5, 10, 6, 8, 9];
const y = [10, 8, 7, 6, 9];
twoSampleTTest(x, y);
/**
* Two-Sample t-test
*
* ┌─────────┬───────┬──────┬────────────────────┐
* │ (index) │ Count │ Mean │ Standard Deviation │
* ├─────────┼───────┼──────┼────────────────────┤
* │ 0 │ 5 │ 7.6 │ 2.073644135332772 │
* │ 1 │ 5 │ 8 │ 1.5811388300841898 │
* └─────────┴───────┴──────┴────────────────────┘
* t = -0.34299717028501797
* df = 8
* p-value = 0.7404394537249616
* 95 percent confidence interval:
* [ -3.0892398363379705, 2.28923983633797 ]
* **/