What This Shows: This statistical test (Analysis of Variance) determines whether article quality scores differ significantly across our four research categories. The horizontal bars show mean scores with error bars indicating variability (±1 standard deviation).
Why It Matters: Understanding whether quality varies by category helps interpret our findings. If one category consistently scores lower, it might indicate less mature research in that area, different publication standards, or varying levels of methodological rigor across topics.
How to Interpret: The F-statistic measures between-group vs within-group variance (higher = larger differences). The p-value indicates statistical significance (p < 0.05 means differences are unlikely due to chance). Eta-squared (η²) shows effect size: small < 0.06, medium 0.06-0.14, large > 0.14.
The category effect is statistically significant (p < 0.05), indicating that article quality scores differ meaningfully across research topics. The small effect size suggests this difference is small but detectable.