DELPHI - How to show normal distribution curve (Gaussian)

Typical propability density function (Gaussian distribution).

var
  i : integer;
  iY : double;
  pDN : TDistribution_Normal;
  pSerie : TLineSeries;
begin
  Memo1.Clear;

  /* prepare chart */

  pSerie := TLineSeries( Chart1.Series[0] );
  pSerie.Clear;

  /* prepare distribution data */

  pDN := TDistribution_Normal.Create;
  pDN.Init( 0, 1 );

  for i := 0 to pDN.pIntegral.pY.Count - 1 do
    begin
      { -- get value }

      iY := pDN.pIntegral.pY.GetValue( i );

      pSerie.AddXY( i, iY );
    end;

And here is very important TDistribution_Normal.Init() function with parameters as MEAN and SIGMA, here is generated range MEAN +-3.5 SIGMA.
The sum values under curve is equeal to 1.

function TDistribution_Normal.Init( _iMean, _iSigma : double ) : boolean;
var
  i : integer;
  iFrom, iTo, iValue : double;
begin
  result := false;

  { -- check }

  if _iSigma <= 0 then
    begin
      ShowMessage( 'Distribution_Normal() - standard deviation can`t be 0.' );
      exit;
    end;

  { -- add range -3.5 sigma - Mean - + 3.5 sigma }

  pIntegral.Clear;

  iFrom := _iMean - ( 3.5 * _iSigma );
  iTo := _iMean + ( 3.5 * _iSigma );
  { aproximation - 300 items }
  pIntegral.iStep := ( iTo - iFrom ) / 300;
  pIntegral.SetInterval( iFrom, iTo );

  { -- calc values normal distribution for every X }

  for i := 0 to pIntegral.pX.Count - 1 do
    begin
      iValue := ( 1 / ( _iSigma * sqrt( 2*pi ) ) ) * 
                exp( - ( sqr( pIntegral.pX.GetValue( i ) - _iMean ) ) / 
                ( 2 * sqr( _iSigma ) ) );

      pIntegral.pY.AddValue( iValue );
    end;

  pIntegral.Calc;

  result := true;
end;

Output: