grammar and formatting

docs/performance-scoring.md

@@ -1,38 +1,39 @@
 # Goal
 
-The goal of this document is to explain how performance scoring on Lighthouse works, and how to understand what to do to improve your Lighthouse performance score. 
+The goal of this document is to explain how performance scoring on Lighthouse works and what to do to improve your Lighthouse performance score. 
 
 # What performance metrics does Lighthouse measure?
 
-Lighthouse primarily measures the following performance metrics: 
+Lighthouse measures the following performance metrics: 
 
-- [First meaningful paint](https://developers.google.com/web/tools/lighthouse/audits/first-meaningful-paint): first meaningful paint is defined as when the browser first puts any “meaningful” element/set of “meaningful” elements  on the screen. What is meaningful is determined from a series of heuristics. 
+- [First meaningful paint](https://developers.google.com/web/tools/lighthouse/audits/first-meaningful-paint): first meaningful paint is defined as when the browser first puts any “meaningful” element/set of “meaningful” elements on the screen. What is meaningful is determined from a series of heuristics. 
 - [First interactive](https://developers.google.com/web/tools/lighthouse/audits/first-interactive): first interactive is defined as the first point at which the page could respond quickly to input. It doesn't consider any point in time before first meaningful paint. The way this is implemented is primarily based on heuristics. 
 *Note: this metric is currently in beta, which means that the underlying definition of this metric is in progress.*
-- [Consistently interactive](https://developers.google.com/web/tools/lighthouse/audits/consistently-interactive): defined as that everything is loaded such that the page will quickly respond to any user input throughout the page. 
+- [Consistently interactive](https://developers.google.com/web/tools/lighthouse/audits/consistently-interactive): defined as the first point at which everything is loaded such that the page will quickly respond to any user input throughout the page. 
 *Note: this metric is currently in beta, which means that the underlying definition of this metric is in progress.*
-- [Perceptual Speed Index (pSI](https://developers.google.com/web/tools/lighthouse/audits/speed-index)): pSI measures how many pixels are painted at each given time interval on the viewport. The fewer the pixels that are painted, the better since we want an experience where most of the content is shown on the screen during the first few moments of initiating the page load. Therefore, the lower the pSI score, the better. 
-- [Estimated Input Latency](https://developers.google.com/web/tools/lighthouse/audits/estimated-input-latency):  this audit measures how fast your app is in responding to user input. Our benchmark is that the estimated input latency should be under 50 ms (see documentation here as to why)
+- [Perceptual Speed Index (pSI)](https://developers.google.com/web/tools/lighthouse/audits/speed-index): pSI measures how many pixels are painted at each given time interval on the viewport. The fewer the pixels that are painted, the better since we want an experience where most of the content is shown on the screen during the first few moments of initiating the page load. Therefore, the lower the pSI score, the better. 
+- [Estimated Input Latency](https://developers.google.com/web/tools/lighthouse/audits/estimated-input-latency):  this audit measures how fast your app is in responding to user input. Our benchmark is that the estimated input latency should be under 50 ms (see documentation here as to why).
 
-*Note that by Lighthouse can experience weird behaviors when it run in the presence of anti-virus scanners and and other extensions or programs that interface with page load. Please try to run without  anti-virus scanners or other extensions/programs to get the cleanest results.*
+*Note that Lighthouse can experience weird behaviors when it runs in the presence of anti-virus scanners and other extensions or programs that interfere with page load. Please try to run without anti-virus scanners or other extensions/programs to get the cleanest results.*
 
 # How are the scores weighted?
 Lighthouse returns a performance score from 0-100. A score of 0 usually indicates an error with performance measurement (so file an issue in the Lighthouse repo if further debugging is needed), and 100 is the best possible ideal score (really hard to get). 
-We usually recommend that if developers are scoring around a 95, their websites are extremely performant. Any additional improvements to the score past 95 doesn’t add additional value for the developer, so we don’t recommend they invest further time to improve the score. 
+If developers are scoring around a 95, their websites are extremely performant. Any additional improvements to the score past 95 doesn’t add additional value for the developer, so we don’t recommend they invest further time to improve the score. 
 
 The performance score is determined from the performance metrics only. The Opportunities/Diagnostics sections do not directly contribute to the performance score.
 
 The metric results are not weighted equally. Currently the weights are:
-5X - first meaningful paint
-5X - first interactive
-5X - consistently interactive
-1X - perceptual speed index
-1X - estimated input latency
+
+* 5X - first meaningful paint
+* 5X - first interactive
+* 5X - consistently interactive
+* 1X - perceptual speed index
+* 1X - estimated input latency
 
 Currently, these weights were determined based on heuristics, and the Lighthouse team is working on formalizing this approach through more field data.  
 
 # How do you determine the optimal and median value calculated?
-Looking at the distribution of metrics like Time to Consistently Interactive (TTCI) over the HTTPArchive dataset, we've seen that the median value of this distribution ends up being around 10 seconds, which is why the value of 12 seconds exists within the dataset. Given that we want to encourage web developers to build fast websites, we've shifted the median slightly to the left by 2 seconds to give a final median value of 10 seconds. Similarly, for the optimal value, we look at the curve to see where the curve flattens out, since that means you're already in top 2% of all websites out there, and the return on investment might not yield additional significant benefits. For example, our optimal values for TTCI is around 3 seconds. 
+Looking at the distribution of metrics like Time to Consistently Interactive (TTCI) over the HTTPArchive dataset, we've seen that the median value of this distribution ends up being around 12 seconds. Given that we want to encourage web developers to build fast websites, we've shifted the median slightly to the left by 2 seconds to give a final median value of 10 seconds. Similarly, for the optimal value, we look at the curve to see where the curve flattens out, since that means you're already in top 2% of all websites out there, and the return on investment might not yield additional significant benefits. For example, our optimal values for TTCI is around 3 seconds. 
 
 
 # What can developers do to improve their performance metrics?