In aquaculture research, independent variables are qualitative (with or without a structure), quantitative, or factorial combinations. A qualitative independent variable is a variable that has unquantifiable, nominal variants (levels), which represent different categories such as the fish gender. The structure in a qualitative independent variable refers to the existence of a relation between its different variants, in a way that suggests that some variants can be grouped together and then compared to other groups of variants. A quantitative independent variable is a variable with measurable variants that are expressed numerically and are fixed throughout the experiment, such as water temperatures. In a study with one independent variable, each variant of this variable represents a treatment. In a study with two or more independent variables, also called a factorial or multifactorial experiment, the treatments represent all the possible combinations of the two or more independent variables. Following an analysis of variance (ANOVA) (or a multiple factor ANOVA) showing that there is a significant difference among the three or more treatment means, a multiple comparison test, an orthogonal contrast procedure, or a polynomial contrast procedure is applied to separate or present the relationship among the treatment means, in accordance with the nature and structure of the independent variable. The use of multiple comparison tests such as Least Significant Difference, Duncan's Multiple Range, Tukey's Honest Significant Difference, Bonferroni and Scheffé's tests, is more relevant when there is no structure in the qualitative independent variable; otherwise the use of the orthogonal contrast procedure, which allows the comparison of related treatment means or groups of means to other treatment means, is more appropriate. The orthogonal contrast procedure is also appropriate for factorial experiments. With quantitative independent variables, the use of polynomial procedure, which detects the trend of the relationship or regression that exists between the independent and response variables, is appropriate. The present paper critically analyzed the statistical methods used in articles published in ten selected international peer-reviewed aquaculture journals in the year 2013. This analysis showed that in none of the studies in which the independent variable was qualitative with a structure, the data have been analyzed using orthogonal contrast procedure. Also, the data of only 34% of the studies in which the independent variable was quantitative have been analyzed using polynomial contrast (regression), whereas the data of only 13% of studies with a factorial design have been analyzed using contrast procedure. More attention should be paid on publishing only studies that used appropriate statistical procedures, which conform to the nature of the independent variables of interest.