Fix Typo (#11651)

Author: alai97

docs/feature-management-experimentation/10-getting-started/statistical-approach.md

@@ -37,7 +37,7 @@ The minimum enforced sample size is 10 for fixed horizon testing and 100 for seq
 Harness FME includes out-of-the-box checks to ensure data quality and prevent misinterpretation of results:
 
 * [Review period check](/docs/feature-management-experimentation/experimentation/experiment-results/analyzing-experiment-results/review-period-check) ensures metrics aren't analyzed too soon after a flag rollout.
-* [Sample ratio mismatch (SMR) check](/docs/feature-management-experimentation/experimentation/experiment-results/analyzing-experiment-results/sample-ratio-check) detects uneven user allocation between treatment groups.
+* [Sample ratio mismatch (SRM) check](/docs/feature-management-experimentation/experimentation/experiment-results/analyzing-experiment-results/sample-ratio-check) detects uneven user allocation between treatment groups.
 
 These guardrails help you trust that your experiment results are reliable and not driven by data integrity issues.
 
@@ -55,4 +55,4 @@ This has the following benefits:
 
 * You can define a metric in Split after an experiment is already running. Similar to the scenario above, you might also have data that you tracked during an experiment, but haven't yet defined a metric for in Split. 
 
-  As long as Split has the events tied to a metric in our system, our system allows you to define a metric at any time during the experiment, even after you've started running the test. On the next run of the calculation job, the system will calculate the impact of your experiment on that new metric from when the experiment began regardless of when you defined the metric.
+  As long as Split has the events tied to a metric in our system, our system allows you to define a metric at any time during the experiment, even after you've started running the test. On the next run of the calculation job, the system will calculate the impact of your experiment on that new metric from when the experiment began regardless of when you defined the metric.