Respuesta :
In factorial designs, researchers include more than one independent variable, but they assess each one separately during data analysis. Looking at each independent variable separately involves interaction with all levels of the variable.
Each level of one independent variable, also known as a factor, is combined with each level of the other independent variables in a factorial design to create all possible combinations. Thus, every combination enters the experiment as a condition. The researcher can determine whether the impact of one independent variable depends on the magnitude of another by including multiple independent variables. An interaction between the independent variables is what is happening here. The main effect is said to exist if the dependent variable exhibits a note-worthy difference between various levels of one factor and all other factors. The null case (baseline), from which main effects are assessed, is the absence of change in the dependent variable across factor levels.
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