> ## Documentation Index
> Fetch the complete documentation index at: https://statsig-4b2ff144-kill-dead-node-pages.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# SRM Checks
> Understand how Statsig detects sample ratio mismatch (SRM) and how to debug skewed traffic splits.
## SRM - Sample Ratio Mismatch
Sample ratio mismatch (SRM for short) is when the observed allocation of **unique** users between test groups differs from the expected allocation or "split" of the test. We have a brief [rundown on this topic here](https://www.statsig.com/blog/sample-ratio-mismatch) on our blog.
This is a signal that there could be some unknown bias in the test. This is a major problem because unless you can clearly diagnose the reason for the imbalance, there's not an easy way to know how much this bias impacts your results.
## SRM Checks
Statsig runs SRM checks on all experiments and feature gates as part of our Health Checks (described [here](/experiments-plus/monitor)). We use a Chi-squared test to identify if the split of users between groups is indicative of a Sample Ratio Mismatch.
We automatically analyze data by common dimensions logged by the Statsig SDK to identify potential drivers of SRM. These include sdk\_type, sdk\_version, reason, is\_bot, browser\_name, browser\_version, os, os\_version, and region to identify potential causes.
