fixing nits

Author: Shannon Anahata

develop-docs/application-architecture/dynamic-sampling/extrapolation.mdx

@@ -16,7 +16,7 @@ For high-volume organizations, sampling is a way to control costs and reduce vol
 
 - **Combining different sample rates**: When your endpoints don't have the same sample rate, how are you supposed to know the true p90 when one of your endpoints is sampled at 1% and another at 100%, but all you get is the aggregate of the samples? Extrapolation calculates the true p90 by combining the data from all endpoints, weighted by the sample rate.
 
-**Note:** When a sample rate is too low, there may be a low confidence in the extrapolated data. When this is the case, you should consider increasing the sample rate, widening your time range or filter, or turning off extrapolation. 
+**Note:** When a sample rate is too low, there may be a low confidence in the extrapolated data. When this is the case, you should consider increasing the sample rate, widening your time range or filter, or turning off extrapolation.  
 
 ## How Does Extrapolation Work?
 ![extrapolation =1000x](./images/extrapolated_data_chart.png)
@@ -66,10 +66,7 @@ In new product surfaces, the question of whether to use extrapolated vs. non-ext
     - Some scenarios, like visualizing metrics over time, are based on aggregates, whereas a case of debugging a specific user's problem hinges on actually seeing the specific events. The best mode depends on the intended usage of the product.
 
 ### When to Turn Off Extrapolation
-Sampled data is designed to help you investigate specific events. Here are two common scenarios where it makes the most sense to turn off extrapolation:
-
-1. **When both sample rate and event volume are low**: Extrapolation becomes less reliable in these cases. You can increase your sample rate, widen your time range or filter to improve accuracy, or turn off extrapolation to examine the actual events.
-2. **When you have a high sample rate but still see low event volumes**: In this case, increasing the sample rate won't help capture more data. You could widen your time range or filter to capture more data, or turn off extrapolation. 
+While extrapolation is usually helpful, if you are exclusively looking to confirm your sampling usage or look exclusively at sampled data, you can turn off extrapolation.
 
 You can always increase your sample rate to 100% to examine all events if traffic is too low to be otherwise useful via extrapolation or sampling.
 

docs/concepts/key-terms/extrapolation.mdx

@@ -67,11 +67,7 @@ Extreme values like `min` and `max` aren't extrapolated because they're less sta
 
 ## When to Turn Off Extrapolation
 
-While extrapolation is usually helpful, there are times when you'll want to look at the raw sampled data instead:
-
-**Low sample rate and low event volume**: When both are low, extrapolation becomes less reliable. Sentry will show a warning when confidence is low. You can increase your sample rate, widen your time range, or turn off extrapolation to examine actual captured events.
-
-**Debugging specific events**: If you need to investigate a particular user's experience or trace through actual spans, turn off extrapolation to see exactly what was captured.
+While extrapolation is usually helpful, if you are exclusively looking to confirm your sampling usage or look exclusively at sampled data, you can turn off extrapolation.
 
 You can disable extrapolation using the settings icon above charts in tools like Trace Explorer. Note that with extrapolation off, your metrics will only reflect the sampled data, not your full traffic.
 

docs/product/explore/trace-explorer/index.mdx

@@ -206,15 +206,11 @@ If your sampling rate is **too low** for an accurate extrapolation (for example,
 Even if you sample your spans, **Trace Explorer's extrapolation gives you reasonably accurate answers** for counts, averages, and percentiles -- without you needing to do anything extra.
 
 ### When to Turn Off Extrapolation
-While extrapolation is usually helpful, there are times when you'll want to look at the raw sampled data instead:
-
-**Low sample rate and low event volume**: When both are low, extrapolation becomes less reliable. Sentry will show a warning when confidence is low. You can increase your sample rate, widen your time range, or turn off extrapolation to examine actual captured events.
-
-**Debugging specific events**: If you need to investigate a particular user's experience or trace through actual spans, turn off extrapolation to see exactly what was captured.
+While extrapolation is usually helpful, if you are exclusively looking to confirm your sampling usage or look exclusively at sampled data, you can turn off extrapolation.
 
 You can disable extrapolation using the settings icon above charts in tools like Trace Explorer.
 
-### Controlling Sampling with tracesSampler
+### How to Tweak Client Side Sampling to Fine More Samples
 
 While you can set a uniform sampling rate with `tracesSampleRate`, the `tracesSampler` function gives you fine-grained control over sampling decisions. With `tracesSampler`, you can: