Fill in the blanks to complete the passage about experiments with more than one independent variable. When an experiment tests all possible combinations of more than one independent variable, it is often referred to as a(n) - design. These designs can show that the effect of one independent variable depends on the level of another independent variable, also known as a(n) - effect. These effects typically have two types. If you were to display the data in a line graph, one type would show the data from one independent variable intersecting with the data from the other, or a(n) - interaction. The second type graphed in the same way would show the data points moving away from one another as the dependent variable increases, or a(n) - interaction. mainspreadingcorrelationalfactorialcrossoverinteractionlongitudinal