The Resource Equation Method is a method developed as an alternative to power analysis for the calculation of sample size in animal studies. With this approach, the sample size is calculated based on the error degrees of freedom (DF) in the variance analysis model. In this study, one and two-factor variance analysis models, which are commonly used in animal studies, are discussed. The minimum and maximum sample size required for these models were calculating and presented in tables. While a minimum of 12 and a maximum of 21 animals in total are sufficient for two independent groups (Design 1), and the total number of animals goes up as the number of groups increases. In one factor, repeated-measures experiment design (Design 2), it was observed that the number of animals to be included in the study decreases significantly as the number of repetitions increases. For all factorial designs (Designs 3 and 4), 2 or 3 animals per subgroup were found to be sufficient. Repeat measure experimental designs can be chosen to increase the power of the study without increasing the number of animal/subjects. Statistical power was calculated for different numbers of groups in Design 1, based on their respective minimum and maximum samples sizes and Cohen's effect sizes, and for most cases, power was found to be much lower than 0.80. Statistical power exceeded 0.80 only in the case of very large effect sizes. Therefore, the researcher can test her hypotheses with larger effect sizes to reach 80% power with sample sizes in independent group comparisons. A determined effect size value for animal studies is not available in the literature. According to the results obtained in our study, the effect sizes for the 2 groups are 1.2; 1.5 and 2.0 for 3 or more groups 0.5; 0.7 and 0.9 can be recommended to take as small, medium and large effect sizes, respectively.