diff --git a/data-visualize.qmd b/data-visualize.qmd
index 9ec4972..2ce3218 100644
--- a/data-visualize.qmd
+++ b/data-visualize.qmd
@@ -268,7 +268,7 @@ ggplot(
   geom_smooth()
 ```
 
-We have successfully added a smooth curves, but this plot doesn't look like the plot from @sec-ultimate-goal, which only has one curve for the entire dataset as opposed to separate curves for each of the penguin species.
+We have successfully added smooth curves, but this plot doesn't look like the plot from @sec-ultimate-goal, which only has one curve for the entire dataset as opposed to separate curves for each of the penguin species.
 
 When aesthetic mappings are defined in `ggplot()`, at the *global* level, they're inherited by each of the subsequent geom layers of the plot.
 However, each geom function in ggplot2 can also take a `mapping` argument, which allows for aesthetic mappings at the *local* level.
diff --git a/numbers.qmd b/numbers.qmd
index 70bb66b..8793013 100644
--- a/numbers.qmd
+++ b/numbers.qmd
@@ -523,7 +523,7 @@ lead(x)
 
 You can lead or lag by more than one position by using the second argument, `n`.
 
-### Consecutive identifies
+### Consecutive identifiers
 
 Sometimes you want to start a new group every time some event occurs.
 For example, when you're looking at website data, it's common to want to break up events into sessions, where a session is defined as a gap of more than x minutes since the last activity.
diff --git a/whole-game.qmd b/whole-game.qmd
index 863da8e..b0e1a07 100644
--- a/whole-game.qmd
+++ b/whole-game.qmd
@@ -39,7 +39,7 @@ Five chapters focus on the tools of data science:
 -   Before you can transform and visualize your data, you need to first get your data into R.
     In @sec-data-import you'll learn the basics of getting `.csv` files into R.
 
-Nestled among these chapters that are five other chapters that focus on your R workflow.
+Nestled among these chapters are five other chapters that focus on your R workflow.
 In @sec-workflow-basics, @sec-workflow-pipes, @sec-workflow-style, and @sec-workflow-scripts-projects you'll learn good workflow practices for writing and organizing your R code.
 These will set you up for success in the long run, as they'll give you the tools to stay organised when you tackle real projects.
 Finally, @sec-workflow-getting-help will teach you how to get help to keep learning.