private void InitializeChart()
{
if (this.AssociatedObject.result != null)
{
this.AssociatedObject.result.Text = string.Empty;
}
if (this.AssociatedObject.visible != null)
{
this.AssociatedObject.visible.Visibility = System.Windows.Visibility.Visible;
}
ChartListData data = new ChartListData();
if (this.AssociatedObject.sample1Mean != null && this.AssociatedObject.sample1Variance != null)
{
for (int j = 0; j < 30; j++)
{
//making normally distributed sample with meanOfFirstSeries as Mean, and sqrtVarianceOfFirstSeries as Standard deviation
double p = 1.0 / (30 * 30) + ((double)j) / (30);
double x = this.AssociatedObject.sample1Mean.Value + this.AssociatedObject.sample1Variance.Value * UtilityFunctions.InverseNormalDistribution(p);
//Adds the data point.
data.Add(new ChartPoint(x, 0));
}
ChartHistogramType.SetDrawNormalDistribution(this.AssociatedObject.series1, true);
ChartHistogramType.SetIntervalOfHistogram(this.AssociatedObject.series1, this.AssociatedObject.sample1Mean.Value / 30);
ChartHistogramType.SetSpacing(this.AssociatedObject.series1.Area, this.AssociatedObject.sample1Variance.Value);
}
this.AssociatedObject.series1.Data = data;
data = new ChartListData();
if (this.AssociatedObject.sample2Mean != null && this.AssociatedObject.sample2Variance != null)
{
for (int j = 0; j < 30; j++)
{
//making normally distributed sample with meanOfFirstSeries as Mean, and sqrtVarianceOfFirstSeries as Standard deviation
double p = 1.0 / (30 * 30) + ((double)j) / (30);
double x = this.AssociatedObject.sample2Mean.Value + this.AssociatedObject.sample2Variance.Value * UtilityFunctions.InverseNormalDistribution(p);
//Adds the data point.
data.Add(new ChartPoint(x, 0));
}
ChartHistogramType.SetDrawNormalDistribution(this.AssociatedObject.series2, true);
ChartHistogramType.SetIntervalOfHistogram(this.AssociatedObject.series2, this.AssociatedObject.sample2Mean.Value / 30);
ChartHistogramType.SetSpacing(this.AssociatedObject.series2.Area, this.AssociatedObject.sample2Variance.Value);
}
this.AssociatedObject.series2.Data = data;
}
public void StatisticFormula()
{
if (this.AssociatedObject.series1.Data != null && this.AssociatedObject.series2.Data != null)
{
this.AssociatedObject.result.Text = "Mean = " + BasicStatisticalFormulas.Mean(this.AssociatedObject.series1).ToString() + "\n" +
"Median = " + BasicStatisticalFormulas.Median(this.AssociatedObject.series1).ToString() + "\n" +
"Standard deviation = " + BasicStatisticalFormulas.StandardDeviation(this.AssociatedObject.series1, true).ToString() + "\n" +
"Varianve = " + BasicStatisticalFormulas.Variance(this.AssociatedObject.series1, true).ToString() + "\n" +
"Variance Biased Estimator = " + BasicStatisticalFormulas.VarianceBiasedEstimator(this.AssociatedObject.series1).ToString() + "\n" +
"Variance Unbiased Estimator = " + BasicStatisticalFormulas.VarianceUnbiasedEstimator(this.AssociatedObject.series1).ToString() + "\n" +
"Co Variance = " + BasicStatisticalFormulas.Covariance(this.AssociatedObject.series1, this.AssociatedObject.series2).ToString() + "\n" +
"Co releation = " + BasicStatisticalFormulas.Correlation(this.AssociatedObject.series1, this.AssociatedObject.series2).ToString() + "\n";
ChartHistogramType.SetDrawNormalDistribution(this.AssociatedObject.series2, false);
// ChartHistogramType.SetDrawNormalDistribution(this.AssociatedObject.series1, false);
}
}
