diff --git a/transform.Rmd b/transform.Rmd
index d77fbbc..4adc241 100644
--- a/transform.Rmd
+++ b/transform.Rmd
@@ -630,7 +630,7 @@ flights %>%
   summarise(mean = mean(dep_delay))
 ```
 
-We get a lot of missing values! That's because aggregation functions obey the usual rule of missing values: if there's any missing value in the input, the output will be a missing value. `x %>% f(y)` turns into `f(x, y)`ou'll learn more about aggregation functions in Section 5.7.4. Fortunately, all aggregation functions have an `na.rm` argument which removes the missing values prior to computation:
+We get a lot of missing values! That's because aggregation functions obey the usual rule of missing values: if there's any missing value in the input, the output will be a missing value. `x %>% f(y)` turns into `f(x, y)` you'll learn more about aggregation functions in Section 5.7.4. Fortunately, all aggregation functions have an `na.rm` argument which removes the missing values prior to computation:
 
 ```{r}
 flights %>% 
@@ -731,7 +731,7 @@ batters %>% arrange(desc(ba))
 
 You can find a good explanation of this problem at <http://varianceexplained.org/r/empirical_bayes_baseball/> and <http://www.evanmiller.org/how-not-to-sort-by-average-rating.html>.
 
-### Other summary functions.
+### Other summary functions
 
 Just using means, counts, and sum can get you a long way, but R provides many other useful summary functions: