A Primer on the Statistical Bridge

Abstract

Statistical analysis is often mistaken for either mathematical formula application or data processing. This primer argues for a different view: statistical analysis is the work of building and testing a warranted bridge between realized empirical evidence and formal targets or claims about the world. It introduces the event-spine distinction, generation and inference, and an intuitive idea of the bridge's carrying capacity—the strength and scope of the inference or explanation an analysis can legitimately support. Brief references to the Sally Clark case and Berkeley graduate admissions illustrate why correct mathematics does not guarantee empirical applicability and why a true observation does not explain itself. The primer is designed as an accessible entry point to the fuller Statistical Bridge framework and a companion reading of Statistical Rethinking.