anchor.diff:  In this implemented test the larger variance is always the numerator, therefore the comparison to F<sub>df1,df2,1-(alpha/2)</sub> is used for a two sided test. 
   
   _Important note: The effectiveness of a preliminary test of variances is discussed. 
  -The F-test is extremely sensitive to normality-violations, and even if the samples follow a normal distribution, it often does not detect situations where a t-test should be avoided. 
  -Conditions for the Effectiveness of a Preliminary Test of Variance , C. and E. Markowski, The American Statistician, Vol 44. No. 4, 11/1990_
  +The F-test is extremely sensitive to normality-violations, and even if the samples follow a normal distribution, it often does not detect situations where a t-test should be avoided._ 
   
   References:
   
     - Jürgen Bortz & Christof Schuster, Statistik für Human- und Sozialwissenschaftler (2010) Chapter 8.6
   
  -  - Ronald Ley, F curves have two tails but the F test is a one-tailed two-tailed test (1979)
  +  - Markowski, Conditions for the Effectiveness of a Preliminary Test of Variance (1990)
  +
  +  - Shlomo S. Sawilowsky, The Probable Difference Between Two Means When σ<sub>1</sub><sup>2</sup>≠σ<sub>2</sub><sup>2</sup> (2002)
  +
  +  - Ronald Ley, F curves have two tails but the F test is a one-tailed two-tailed test (1979) + Reviewer comments
     
  -*F-Test from data*
  +*F-Test from data:*
   *)
   
   let sampleFA = vector [|5.0; 6.0; 5.8; 5.7|] 
  
positive.code:     Using a significance level of 0.05 the sample variances do differ significantly.
  *)
  (** 
  *F-Test from given parameters*
  *)
  // sample properties are given as (variance,degree of freedom) 
  let sampleF1 = (0.1, 15.)
  
negative.code: ANOVA provides the user with a global statement if samples differ from each other. It does not provide detailed information regarding
  differences of the single samples.
  
  If the H<sub>0</sub> hypothesis is neglected (so significant differences are assumed), a post hoc test (multiple comparison test) allows the pairwise comparison of the 
  individual groups.
  
  Reference: What is the proper way to apply the multiple comparison test?, Sangseok Lee and Dong Kyu Lee, 2018
  