Recommended effect size interpretations for one-dimensional functional data

We present effect size (Cohen’s d-value) interpretations for functional data that are probabilistically equivalent to conventional interpretation guidelines for scalar data. Results suggest that traditionally “Large” effects occur with a high probability in functional data, and ought to be regarded as “Small” or “Very small” for probabilistic consistency.