diff --git a/data-import.qmd b/data-import.qmd
index cdf3df2..ec31aa0 100644
--- a/data-import.qmd
+++ b/data-import.qmd
@@ -104,7 +104,7 @@ students |> janitor::clean_names()
 ```
 
 Another common task after reading in data is to consider variable types.
-For example, `meal_type` is a categorical variable with a known set of possible values, which in R should be represented as a factor:
+For example, `meal_plan` is a categorical variable with a known set of possible values, which in R should be represented as a factor:
 
 ```{r}
 students |>
@@ -114,7 +114,7 @@ students |>
   )
 ```
 
-Note that the values in the `meal_type` variable have stayed the same, but the type of variable denoted underneath the variable name has changed from character (`<chr>`) to factor (`<fct>`).
+Note that the values in the `meal_plan` variable have stayed the same, but the type of variable denoted underneath the variable name has changed from character (`<chr>`) to factor (`<fct>`).
 You'll learn more about factors in @sec-factors.
 
 Before you analyze these data, you'll probably want to fix the `age` column.