The Sparsity-of-Effects Principle, often associated with the field of statistics and experimental design, suggests that in many situations, only a small number of factors or variables significantly influence the response or outcome of interest. This principle is particularly relevant in contexts where multiple factors can potentially affect a response, such as in a factorial experiment or when creating predictive models.
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