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  • https://stats.libretexts.org/Courses/Kansas_State_University/EDCEP_917%3A_Experimental_Design_(Yang)/03%3A_Between-Subjects_Factorial_Design/3.03%3A_Factorial_ANOVA_-_Interaction_Effects
    In the top panel, independent variable “B” has an effect at level 1 of independent variable “A” (there is a difference in the height of the blue and red bars on the left side of the graph) but no effe...In the top panel, independent variable “B” has an effect at level 1 of independent variable “A” (there is a difference in the height of the blue and red bars on the left side of the graph) but no effect at level 2 of independent variable “A.” (there is no difference in the height of the blue and red bars on the right side of the graph).
  • https://stats.libretexts.org/Courses/Kansas_State_University/EDCEP_917%3A_Experimental_Design_(Yang)/03%3A_Between-Subjects_Factorial_Design/3.02%3A_Factorial_ANOVA_-_Main_Effects
    The results of between-subjects factorial designs with two independent variables can be graphed by representing one independent variable on the x-axis and representing the other by using different col...The results of between-subjects factorial designs with two independent variables can be graphed by representing one independent variable on the x-axis and representing the other by using different colored bars or lines. (The y-axis is always reserved for the dependent variable.) Figure \(\PageIndex{1}\) shows results for two hypothetical factorial experiments.

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