/**
* Returns the moments of the distribution
*
* @param string $moments Which moments to compute. m for mean, v for variance, s for skew, k for kurtosis. Default 'mv'
* @return type array A dictionary containing the first four moments of the distribution
*/
public function stats($moments = 'mv')
{
return $this->calculator->getStats($moments, $this->df);
}
/**
* Two Sample T Test
*
* The two-sample T test tests whether two samples are significantly
* different from each other.
*
* @param array $datax The first sample to test
* @param array $datay The second sample to test
* @return float The probability of having the first sample's population mean be greater than or equal to the second sample's population mean
*/
public function twoSampleTTest(array $datax, array $datay)
{
$df = pow(pow($this->basic->sampleStddev($datax), 2) / count($datax) + pow($this->basic->sampleStddev($datay), 2) / count($datay), 2) / (pow(pow($this->basic->sampleStddev($datax), 2) / count($datax), 2) / (count($datax) - 1) + pow(pow($this->basic->sampleStddev($datay), 2) / count($datay), 2) / (count($datay) - 1));
$sampleT = ($this->basic->average($datax) - $this->basic->average($datay)) / sqrt(pow($this->basic->sampleStddev($datax), 2) / count($datax) + pow($this->basic->sampleStddev($datay), 2) / count($datay));
return $this->stu->getCdf($sampleT, $df);
}
