anchor.diff:  *)
   module GoodnessOfFit =    
       open FSharp.Stats
  -  
  +    open System
       /// Three sum of squares 
       type SumOfSquares = {
  -        /// Regression sum of squares (SSR - explained) 
  +        /// Regression sum of squares (SSR: explained); Sum((yFit-yMean)**2.)
           Regression : float
  -        /// Error sum of squares (SSE - unexplained)
  +        /// Error sum of squares (SSE: unexplained); residual sum of squares; Sum((y-yFit)**2.)
           Error      : float        
  -        /// Total sum of squares (SST - total)
  +        /// Total sum of squares (SST: total); Sum((y-yMean)**2.)
           Total      : float        
           SSxx       : float
           SSxy       : float
  
positive.code: 
      /// Standard deviation of y(x) 
      // Square root of variance s2y,x
      let stDevY (sumOfSquares:SumOfSquares) =
          sumOfSquares.Error / (sumOfSquares.Count - 2.) |> sqrt
  
      /// Standard deviation of slope (beta)    
      let stDevSlope (sumOfSquares:SumOfSquares) =
          ( sumOfSquares.Error / (sumOfSquares.Count - 2.) ) / sumOfSquares.SSxx
  
      /// Standard deviation of intercept (alpha)
      let stDevIntercept (sumOfSquares:SumOfSquares) =
           let s2yx = sumOfSquares.Error / (sumOfSquares.Count - 2.) 
           let mx2  = sumOfSquares.MeanX*sumOfSquares.MeanX
           s2yx * ((1./sumOfSquares.Count) + (mx2/sumOfSquares.SSxx))
          
  
      let ttestSlope slope (sumOfSquares:SumOfSquares) =
          let sb = stDevSlope sumOfSquares |> sqrt
          let statistic =  slope / sb 
          let TTest = Testing.TestStatistics.createTTest statistic (sumOfSquares.Count - 2.)
          TTest
  
      let ttestIntercept intercept (sumOfSquares:SumOfSquares) =
          let si = stDevIntercept sumOfSquares |> sqrt
          let statistic =  intercept / si 
          let TTest = Testing.TestStatistics.createTTest statistic (sumOfSquares.Count - 2.)
          TTest
  
negative.code:                         raise (System.ArgumentException("Coefficient has to be [a;b]!"))
                      let fitFunction x = coef.[0] + coef.[1] * x 
                      calculateANOVA 1 fitFunction x_data y_data 
                  
          module Polynomial = 
  
              //http://www.wolframalpha.com/input/?i=Vandermonde%20matrix&lk=1&a=ClashPrefs_%2aMathWorld.VandermondeMatrix-
  