| 1 | import mean from "./mean";
|
| 2 | import standardDeviation from "./standard_deviation";
|
| 3 |
|
| 4 | /**
|
| 5 | * This is to compute [a one-sample t-test](https://en.wikipedia.org/wiki/Student%27s_t-test#One-sample_t-test), comparing the mean
|
| 6 | * of a sample to a known value, x.
|
| 7 | *
|
| 8 | * in this case, we're trying to determine whether the
|
| 9 | * population mean is equal to the value that we know, which is `x`
|
| 10 | * here. usually the results here are used to look up a
|
| 11 | * [p-value](http://en.wikipedia.org/wiki/P-value), which, for
|
| 12 | * a certain level of significance, will let you determine that the
|
| 13 | * null hypothesis can or cannot be rejected.
|
| 14 | *
|
| 15 | * @param {Array<number>} x sample of one or more numbers
|
| 16 | * @param {number} expectedValue expected value of the population mean
|
| 17 | * @returns {number} value
|
| 18 | * @example
|
| 19 | * tTest([1, 2, 3, 4, 5, 6], 3.385).toFixed(2); // => '0.16'
|
| 20 | */
|
| 21 | function tTest(x, expectedValue) {
|
| 22 | // The mean of the sample
|
| 23 | const sampleMean = mean(x);
|
| 24 |
|
| 25 | // The standard deviation of the sample
|
| 26 | const sd = standardDeviation(x);
|
| 27 |
|
| 28 | // Square root the length of the sample
|
| 29 | const rootN = Math.sqrt(x.length);
|
| 30 |
|
| 31 | // returning the t value
|
| 32 | return (sampleMean - expectedValue) / (sd / rootN);
|
| 33 | }
|
| 34 |
|
| 35 | export default tTest;
|