Abstract

A lot of toxicological testing is done to learn about toxicity in aquatic environments. This kind of experiment, whose response variable is determined by counts, may have reproduction as one of its endpoints. There is research on the best probability distribution to utilise for the data analysis. The assumption of this probability distribution is crucial to the theory of optimum experimental design, and when it is incorrect, the produced design may be less efficient. The major goal of this work is to suggest reliable designs when the probability distribution of the response variable is unknown. In order to accomplish this, three distinct approaches are introduced, contrasted, and then used in toxicological testing based on Ceriodaphnia dubia.