THE DATA WE WILL USE

Let me introduce a set of fictitious data we will use in all the simulations. They are in arbitrary units, indicating that they can be any short of experimental signal. In this case, I consider an EFFECT and not a RESPONSE or a normalized inhibition (e.g. cell viability, % of death cells, etc) as a more general case easily extensible to it. I consider three experiments with a Negative Control group (e.g. unexposed cells) and four growing concentrations of a toxicant (C1-C2-C3-C4). Each condition has n=5 replicates. Experiment 1: C: 50-65-72-66-57; C1: 102-79-83-95-69; C2: 121-116-99-107-112; C3: 118-130-135-150-115; C4: 121-137-140-155-125. Experiment 2: C: 63-67-81-82-70; C1: 75-89-92-88-90; C2: 99-95-110-89-103; C3: 108-121-105-118-130; C4: 108-121-119-130-135. Experiment 3: C: 101-72-66-88-91; C1: 90-99-89-105-115; C2: 115-132-108-121-116; C3: 130-142-149-130-137; C4: 140-149-160-150-147. Note that the number of replicates is too low to test the normality, but it is a typical case of possible data from literature, with typical n of both experiments and replicates. However, no particular outliers are present along each experiment, indicating that the parametric approach is acceptable. Therefore, we will proceed with parametric statistics. However, I will indicate when possible non-parametric alternatives when the presence of particularly variable values/outliers may make the parametric statistics inadequate.