Review suggestions

Author: 46bit

src/content/docs/analytics/analytics-engine/sampling.mdx

@@ -70,7 +70,7 @@ Here are some examples of how to express some common queries over sampled data.
 | Count events in a dataset          | `count()`                | `sum(_sample_interval)`                                 |
 | Sum a quantity, for example, bytes | `sum(bytes)`             | `sum(bytes * _sample_interval)`                         |
 | Average a quantity                 | `avg(bytes)`             | `sum(bytes * _sample_interval) / sum(_sample_interval)` |
-| Compute quantiles                  | `quantile(0.50)(bytes)`  | `quantileWeighted(0.50)(bytes, _sample_interval)`       |
+| Compute quantiles                  | `quantile(0.50)(bytes)`  | `quantileExactWeighted(0.50)(bytes, _sample_interval)`  |
 
 Note that the accuracy of results is not determined by the sample interval, similar to the mapping analogy mentioned earlier. A high sample interval can still provide precise results. Instead, accuracy depends on the total number of data points queried and their distribution.
 

src/content/docs/analytics/analytics-engine/sql-api.mdx

@@ -32,7 +32,7 @@ Use the dashboard to create a token with permission to read analytics data on yo
 
 ## Querying the API
 
-Submit the query text in the body of a `POST` request to the API address. The format of the data returned can be selected using the [`FORMAT` option](/analytics/analytics-engine/sql-reference/statements/#format-clause) in your query.
+Submit the query text in the body of a `POST` request to the API address. The format of the data returned can be selected using the [`FORMAT`](/analytics/analytics-engine/sql-reference/statements/#format-clause) option in your query.
 
 You can use cURL to test the API as follows, replacing the `<account_id>` with your 32 character account ID (available in the dashboard) and the `<token>` with the token string you generated above.
 
@@ -82,7 +82,7 @@ The rate at which the data is sampled is exposed via the `_sample_interval` colu
 | `SELECT SUM(double1) FROM ...` | `SELECT SUM(_sample_interval * double1) FROM ...`                         |
 | `SELECT AVG(double1) FROM ...` | `SELECT SUM(_sample_interval * double1) / SUM(_sample_interval) FROM ...` |
 
-Additionally, the [QUANTILEWEIGHTED function](/analytics/analytics-engine/sql-reference/aggregate-functions/#quantileweighted) is designed to be used with sample interval as the third argument.
+Additionally, the [QUANTILEEXACTWEIGHTED](/analytics/analytics-engine/sql-reference/aggregate-functions/#quantileexactweighted) function is designed to be used with sample interval as the third argument.
 
 ## Example queries
 

src/content/docs/analytics/analytics-engine/sql-reference/aggregate-functions.mdx

@@ -20,9 +20,9 @@ count()
 count(DISTINCT column_name)
 ```
 
-Count is an aggregation function that returns the number of rows in each group or results set.
+`count` is an aggregation function that returns the number of rows in each group or results set.
 
-Count can also be used to count the number of distinct (unique) values in each column:
+`count` can also be used to count the number of distinct (unique) values in each column:
 
 Example:
 
@@ -41,7 +41,7 @@ Usage:
 sum([DISTINCT] column_name)
 ```
 
-Sum is an aggregation function that returns the sum of column values across all rows in each group or results set. Sum also supports `DISTINCT`, but in this case it will only sum the unique values in the column.
+`sum` is an aggregation function that returns the sum of column values across all rows in each group or results set. Sum also supports `DISTINCT`, but in this case it will only sum the unique values in the column.
 
 Example:
 

src/content/docs/analytics/analytics-engine/sql-reference/mathematical-functions.mdx

@@ -19,7 +19,7 @@ Usage:
 intDiv(a, b)
 ```
 
-Divide a by b, rounding the answer down to the nearest whole number.
+Divide `a` by `b`, rounding the answer down to the nearest whole number.
 
 ## log <Badge text="New" variant="tip" size="small" />
 

src/content/docs/analytics/analytics-engine/sql-reference/string-functions.mdx

@@ -205,7 +205,7 @@ Examples:
 SELECT format('blob1: {}', blob1) AS s FROM dataset;
 ```
 
-See also: [formatDateTime](/analytics/analytics-engine/sql-reference/date-time-functions/#formatdatetime)
+The [formatDateTime](/analytics/analytics-engine/sql-reference/date-time-functions/#formatdatetime) function might also be useful.
 
 ## extract
 

src/content/docs/analytics/analytics-engine/worker-querying.mdx

@@ -39,7 +39,7 @@ const response = await fetch(API, {
 const responseJSON = await response.json();
 ```
 
-The data will be returned in the format described in the [FORMAT section of the API docs](/analytics/analytics-engine/sql-reference/statements/#json) allowing you to extract meta information about the names and types of returned columns in addition to the data itself and a row count.
+The data will be returned in the format described in the [FORMAT](/analytics/analytics-engine/sql-reference/statements/#json) section of the documentation, allowing you to extract meta information about the names and types of returned columns in addition to the data itself and a row count.
 
 ## Example Worker