diff --git a/RELEASING/release-notes-2-0/README.md b/RELEASING/release-notes-2-0/README.md
index 265dd32941..617159100d 100644
--- a/RELEASING/release-notes-2-0/README.md
+++ b/RELEASING/release-notes-2-0/README.md
@@ -34,7 +34,7 @@ Superset 2.0 is a big step forward. This release cleans up many legacy code path
 
 - New GitHub workflow to test Storybook Netlify instance nightly ([#19852](https://github.com/apache/superset/pull/19852))
 
-- Minimum requirement for Superset is now Python 3.8 ([#19017](https://github.com/apache/superset/pull/19017)
+- Minimum requirement for Superset is now Python 3.8 ([#19017](https://github.com/apache/superset/pull/19017))
 
 ## Features
 
diff --git a/docs/docs/frequently-asked-questions.mdx b/docs/docs/frequently-asked-questions.mdx
index 3007584ab1..8c9fa034cf 100644
--- a/docs/docs/frequently-asked-questions.mdx
+++ b/docs/docs/frequently-asked-questions.mdx
@@ -154,7 +154,7 @@ Table schemas evolve, and Superset needs to reflect that. It’s pretty common i
 dashboard to want to add a new dimension or metric. To get Superset to discover your new columns,
 all you have to do is to go to **Data -> Datasets**, click the edit icon next to the dataset
 whose schema has changed, and hit **Sync columns from source** from the **Columns** tab.
-Behind the scene, the new columns will get merged it. Following this, you may want to re-edit the
+Behind the scene, the new columns will get merged. Following this, you may want to re-edit the
 table afterwards to configure the Columns tab, check the appropriate boxes and save again.
 
 ### What database engine can I use as a backend for Superset?
@@ -220,7 +220,7 @@ and write your own connector. The only example of this at the moment is the Drui
 is getting superseded by Druid’s growing SQL support and the recent availability of a DBAPI and
 SQLAlchemy driver. If the database you are considering integrating has any kind of of SQL support,
 it’s probably preferable to go the SQLAlchemy route. Note that for a native connector to be possible
-the database needs to have support for running OLAP-type queries and should be able to things that
+the database needs to have support for running OLAP-type queries and should be able to do things that
 are typical in basic SQL:
 
 - aggregate data
diff --git a/docs/docs/installation/event-logging.mdx b/docs/docs/installation/event-logging.mdx
index e6b0f8b356..f5dcb53c8d 100644
--- a/docs/docs/installation/event-logging.mdx
+++ b/docs/docs/installation/event-logging.mdx
@@ -56,5 +56,5 @@ from superset.stats_logger import StatsdStatsLogger
 STATS_LOGGER = StatsdStatsLogger(host='localhost', port=8125, prefix='superset')
 ```
 
-Note that it’s also possible to implement you own logger by deriving
+Note that it’s also possible to implement your own logger by deriving
 `superset.stats_logger.BaseStatsLogger`.