/** * Compute standard deviation. * * @param array $a The array of data to find the standard deviation for. * Note that all values of the array will be cast to float. * @param bool $is_sample [Optional] Indicates if $a represents a sample of the * population (otherwise its the population); Defaults to false. * @return string|bool The standard deviation or false on error. */ function stddev(array $a, $is_sample = false) { if (math_count($a) < 2) { trigger_error("The array has too few elements", E_USER_NOTICE); return false; } return bcsqrt(variance($a, $is_sample)); }
function stddev($values) { return sqrt(variance($values)); }
function ecart_type($tabval) { return(sqrt(variance($tabval))); }
function stdev($array) { $stdev = sqrt(variance($array)); return $stdev; }
function stdev($a) { return sqrt(variance($a)); }
function standard_deviation($nums) { return sqrt(variance($nums)); }
echo ' </ul>' . "\n"; } else { if ($nbcards != 0 && $nbimages == 0) { echo ' <strong>All</strong>' . "\n"; } else { echo ' <i>None</i>' . "\n"; } } echo ' </td>' . "\n"; if ($nbimages == 0) { echo ' <td colspan="3">N/A</td>' . "\n"; } else { $meansize = round($foldersize / $nbimages); echo ' <td>' . human_filesize($foldersize) . '</td>' . "\n"; echo ' <td style="background-color: ' . nb2html(round($meansize / 1024)) . ' !important ;">' . human_filesize($meansize) . '</td>' . "\n"; $variance = round(variance($filesizes)); $cv = round((5000 - $variance) / 20); echo ' <td style="background-color: ' . nb2html($cv) . ' !important ;">' . $variance . '</td>' . "\n"; } echo ' </tr>' . "\n"; unset($exts[$arr['se']]); } function nb2html($nb, $max = 255) { $nb = min($nb, $max); // $nb can't be > $max $mid = $max / 2; $r = $g = $b = 0; if ($nb <= $mid) { $r = 255; $g = 2 * $nb;