public DiscreteStatisticalInfo(string sampleNum, List <float> values)
{
this.SampleNum = sampleNum;
StatValue sv = StatDatas.GetStateValue(values);
this.Count = sv.N.ToString();
this.Average = sv.MEAN.ToString("#0.0000");
this.StandardDeviation = sv.SD.ToString("#0.0000");
this.CVValue = (sv.CV * 100).ToString("#0.00") + "%";
this.Range = sv.R.ToString("#0.0000");
}
public static StatValue GetStateValue(List <float> values)
{
StatValue V = new StatValue();
V.N = values.Count;
V.MEAN = 0;
V.SD = 0;
V.CV = 0;
V.R = 0;
if (values.Count == 0)
{
return(V);
}
float Min = values.ElementAt(0);
float Max = values.ElementAt(0);
float Sum = 0;
foreach (float value in values)
{
if (value > Max)
{
Max = value;
}
if (value < Min)
{
Min = value;
}
Sum += value;
}
V.MEAN = (float)(((int)(Sum / V.N * 10000)) / 10000.0000);
if (V.N <= 1)
{
V.SD = 0;
V.CV = 0;
V.R = 0;
}
else
{
float TSum = 0;
foreach (float value in values)
{
//float sun = (float)(((int)(((float)((int)(((float)(((int)(value * 10000)) / 10000.0000) - V.MEAN) * 10000) / 10000.0000) * (float)((int)(((float)(((int)(value * 10000)) / 10000.0000) - V.MEAN) * 10000) / 10000.0000)) * 10000)) / 10000.0000);
//TSum = sun + (float)((int)(TSum * 10000) / 10000.0000);
TSum += (value - V.MEAN) * (value - V.MEAN);
}
V.SD = (float)((int)(Math.Sqrt(TSum / (V.N - 1)) * 10000) / 10000.0000);
V.CV = V.SD / V.MEAN;
V.R = Max - Min;
}
return(V);
}
