Significance tests don’t create meaning… your design does. If your factor levels are cosmetic, ANOVA will dutifully compare cosmetics. The craft is identifying the construct that actually moves outcomes… then operationalizing it cleanly. Don’t toggle the nearest proxy; name the lever and build conditions that differ on that lever (not five things at once). Before collecting a single datum, write this sentence: “Our independent variable is ___, and conditions differ only in ___.” Then pressure-test it: Could a reasonable critic argue the groups also differ in motivation, time-on-task, or demand characteristics? Tighten procedures until “between-groups” reflects the story you intend to tell. Pair that with noise hygiene (counterbalancing, consistent instructions) to keep “within-groups” honest. ANOVA can detect differences… but only if you invite them with a design that isolates the mover. Stats amplify design… they don’t rescue it.
