Is a comparison of results meaningful from the inexact replications of computational experiments?

While performing statistical tests [7] the first question is which statistical test, parametric or non-parametric, is suitable. It is well known that parametric tests have much more power (probability that a statistical test will correctly reject a false null hypothesis, or a probability of avoiding a Type II error) than a non-parametric test. Hence, we should use parametric tests whenever allowed. Conditions for parametric statistical tests are independence, normality, and homoscedasticity [7]. Since we do not have access to raw data of the experiments performed by Waghmare in [8] we can only check normality (e.g., by Kolmogorov-Smirnov test [7]) of our own raw data and make a