# tablepress/3.4/libraries/vendor/PhpSpreadsheet/Calculation/Statistical/Distributions/F.php

TablePress – Tables in WordPress made easy, version 3.4. 75 lines.

- Page: https://pluginprobe.com/plugins/tablepress/3.4/code/libraries/vendor/PhpSpreadsheet/Calculation/Statistical/Distributions/F.php
- Raw: https://pluginprobe.com/plugins/tablepress/3.4/raw/libraries/vendor/PhpSpreadsheet/Calculation/Statistical/Distributions/F.php
- Modified: 2026-09-30T03:50:46+00:00

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```php
<?php

namespace TablePress\PhpOffice\PhpSpreadsheet\Calculation\Statistical\Distributions;

use TablePress\PhpOffice\PhpSpreadsheet\Calculation\ArrayEnabled;
use TablePress\PhpOffice\PhpSpreadsheet\Calculation\Exception;
use TablePress\PhpOffice\PhpSpreadsheet\Calculation\Information\ExcelError;

class F
{
	use ArrayEnabled;

	/**
	 * F.DIST.
	 *
	 *    Returns the F probability distribution.
	 *    You can use this function to determine whether two data sets have different degrees of diversity.
	 *    For example, you can examine the test scores of men and women entering high school, and determine
	 *        if the variability in the females is different from that found in the males.
	 *
	 * @param mixed $value Float value for which we want the probability
	 *                      Or can be an array of values
	 * @param mixed $u The numerator degrees of freedom as an integer
	 *                      Or can be an array of values
	 * @param mixed $v The denominator degrees of freedom as an integer
	 *                      Or can be an array of values
	 * @param mixed $cumulative Boolean value indicating if we want the cdf (true) or the pdf (false)
	 *                      Or can be an array of values
	 *
	 * @return array<mixed>|float|string If an array of numbers is passed as an argument, then the returned result will also be an array
	 *            with the same dimensions
	 */
	public static function distribution($value, $u, $v, $cumulative)
	{
		if (is_array($value) || is_array($u) || is_array($v) || is_array($cumulative)) {
			return self::evaluateArrayArguments([self::class, __FUNCTION__], $value, $u, $v, $cumulative);
		}

		try {
			$value = DistributionValidations::validateFloat($value);
			$u = DistributionValidations::validateInt($u);
			$v = DistributionValidations::validateInt($v);
			$cumulative = DistributionValidations::validateBool($cumulative);
		} catch (Exception $e) {
			return $e->getMessage();
		}

		if ($value < 0 || $u < 1 || $v < 1) {
			return ExcelError::NAN();
		}

		if ($cumulative) {
			$adjustedValue = ($u * $value) / ($u * $value + $v);

			return Beta::incompleteBeta($adjustedValue, $u / 2, $v / 2);
		}

		if ($value == 0.0) {
			if ($u === 2) {
				return 1.0;
			}

			return ($u === 1) ? INF : 0.0;
		}

		// Log domain, so large degrees of freedom cannot overflow the Gamma ratio.
		return exp(
			Gamma::logGamma(($v + $u) / 2) - Gamma::logGamma($u / 2) - Gamma::logGamma($v / 2)
			+ ($u / 2) * log($u / $v)
			+ (($u - 2) / 2) * log($value)
			- (($u + $v) / 2) * log(1 + ($u / $v) * $value)
		);
	}
}

```