anchor.diff:      |]
   
   let contrastMatrix = 
  -    [| [|1.0;-1.0;0.0;0.0;|] ; [|1.0;0.0;-1.0;0.0;|] ; [|1.0;0.;0.0;-1.0;|] ; 
  -    [|0.0;1.0;-1.0;0.0;|]    ; [|0.0;1.0;0.0;-1.0;|] ;
  +    [| 
  +    [|1.0;-1.0;0.0;0.0;|]
  +    [|1.0;0.0;-1.0;0.0;|]
  +    [|1.0;0.0;0.0;-1.0;|]
  +    [|0.0;1.0;-1.0;0.0;|]
  +    [|0.0;1.0;0.0;-1.0;|]
       [|0.0;0.0;1.0;-1.0;|]
       |]
   
  
positive.code: 
  Anova.oneWayAnova dmg
  
  
  //TukeyHSD contrastMatrixDmg dmg 
  // https://brownmath.com/stat/anova1.htm
  
  let dsd = 
      [|
       //[|7.;4.;6.;8.;6.;6.;2.;9.|];
       //[|5.;5.;3.;4.;4.;7.;2.;2.|];
       //[|2.;4.;7.;1.;2.;1.;5.;5.|] ; 
          [|64.; 72.; 68.; 77.; 56.; 95.;|] ;
          [|78.; 91.; 97.; 82.; 85.; 77.;|] ;
          [|75.; 93.; 78.; 71.; 63.; 76.;|] ;
          [|55.; 66.; 49.; 64.; 70.; 68.;|] ;   
      |]
  
  let contrastMatrixDsd = contrastMatrix //used in docs for "Anova"
  
  Anova.oneWayAnova dsd
  
  tukeyHSD contrastMatrixDsd dsd 
  
  
  let d1 = [159.;179.;100.;45.;384.;230.;100.;320.;80.;220.;320.;210.;]
  let d2 = [14.4;15.2;11.3;2.5;22.7;14.9;1.41;15.81;4.19;15.39;17.25;9.52; ]
      
  
  Testing.FisherHotelling.test d1 d2
  
  //Testing.Hays contrastMatrix 
  
  (**
  <a name="PvalueAdjust"></a>
  
negative.code: let sampleP1 = vector [18.;21.;16.;22.;19.;24.;17.;21.;23.;18.;14.;16.;16.;19.;18.;20.;12.;22.;15.;17.;]
  let sampleP2 = vector [22.;25.;17.;24.;16.;29.;20.;23.;19.;20.;15.;15.;18.;26.;18.;24.;18.;25.;19.;16.;]
  
  let paired = TTest.twoSamplePaired sampleP1 sampleP2
  
  (*
      The test returns a significant p value:
      paired.PValue = 0.00439
  *)
  
  
  (**
  Case 4: Two sample t test with unequal variances (Welch test)
  
  If you are unsure about the nature of the underlying population, you may ask if the theoretical population distributions 
  you want to compare do have the same standard deviations. 
  
  If not the welch test can serve as a appropriate hypothesis test for mean differences.
  
  *)
  
  
  let sampleW1 = vector [0.8;0.9;1.0;1.1;1.2]
  let sampleW2 = vector [0.8;1.1;1.3;1.5;2.0]
  
  let welch = TTest.twoSample false sampleW1 sampleW2
  
  (*
      The test returns a not significant p value:
      welch.PValue = 0.1725626595
  *)
  
  (**
  <a name="ChiSquareTest"></a>
  