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Introduction: The appropriate choice of statistical tools for inferential data analysis is fundamental in science. Thus, identifying the behavior of the observations is essential; to select, with the greatest possible precision, the statistical technique that leads to accurate results and enriching conclusions. Objective: The distribution of raw and residual data from cattle and chicken farming was studied by verifying parametric assumptions; In turn, three statistical methods were compared, by zootechnical species, discussing their plasticity, adjustment and precision. Materials and methods: The following were analyzed in cattle: body condition, live weight, hair length and biochemical constants (calcium, phosphorus, magnesium). In chickens: live weight, breast width, thigh length, crest length, presence of endo and ectoparasites. Tests of normality (Shapiro Wilk and Kolmogorov (Lilliefors)) and homogeneity of variances (Levene) were applied. The inferential methods were considered in bovines: ANOVA with Tukey; Welch's ANOVA with the Games Howell test and Kruskal Wallis with Dunn's test. In birds: the student test, with Welch and Wilcoxon-Mann-Whitney correction. Results: Normality tests maintained similar results. A difference was found in decision criteria between the inferential analyses, for magnesium level and thigh length. Conclusions: It is explicitly recommended, in veterinary and zootechnical studies, with scientific rigor, to analyze the normality and homogeneity of variance, to appropriately identify and know the behavioral pattern of the data coming from the work, in order to properly implement the inferential statistical tool. that will contribute to discriminating chance and causality in the events treated. [ABSTRACT FROM AUTHOR]

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