0

This library entry at msdn.microsoft.com might get you closer to what you're looking for if you're looking for a graphical output based on your data. At the least it should get you closer to what you need even if you need to modify the sample method they provide to fit your needs.

Hope this helps :) Please mark as solved if it resolves your issue.

It is really hot overhere(34°C) but I still managed to do a bit of programming. Having no swimming pool around, what else can a man do? ;)

So here it is, hope it helps.

```
namespace ConsoleApplication1
{
class Program
{
static void Main(string[] args)
{
double[] D = { 5, 2, 7, 8, 11, 12, 3, 1, 2, 10 };
double[] B = { 4, 8 };
double[] F = FREQUENCY(D, B);
for (int i = 0; i < F.Length; i++)
{
Console.WriteLine(F[i]);
}
Console.WriteLine(NORMDIST(1,42,1.5,false));
Console.ReadKey();
}
// QAD, so little error checking
public static double[] FREQUENCY(double[] Data, double[] Bins)
{
double[] FreqList = new double[Bins.Length + 1];
for (int i = 0; i < FreqList.Length; i++)
{
FreqList[i] = 0.0; //init our list
}
for (int i = 0; i < Data.Length; i++)
{
for (int j = 0; j < Bins.Length; j++)
{
if (Data[i] <= Bins[j])
{
FreqList[j]++;
break; // we don't want to fill others
}
}
if (Data[i] > Bins[Bins.Length - 1])
{
FreqList[Bins.Length]++;
}
}
return FreqList;
}
//evaluation of the bell curve. See http://en.wikipedia.org/wiki/Normal_distribution
public static double NORMDIST(double x, double mean, double standard_dev, bool cumulative)
{
double fact = standard_dev * Math.Sqrt(2.0 * Math.PI);
double expo = (x - mean) * (x - mean) / (2.0 * standard_dev * standard_dev);
//if (cumulative) do integration from 0 to x
//look at this snippet for A way not THE way to do this:
//http://www.daniweb.com/code/snippet217197.html
//else just return the value:
return Math.Exp(-expo) / fact;
}
}
}
```

You

This question has already been solved: Start a new discussion instead