Why Safe T-Tests Outperform Classical Methods in Large-Scale Experiments

This article explores the shortcomings of p-values in modern experimentation and introduces safe testing as a powerful, anytime-valid alternative. Through real-world benchmarks and simulations, safe t-tests and safe proportion tests are shown to outperform classical methods like the t-test and χ² test, especially in large-scale A/B testing scenarios. With advantages in speed, flexibility, and interpretability via E-variables, safe testing promises to reshape data-driven decision-making — though widespread adoption will require education and persistence.