diff --git a/vignettes/TQ03-scaling-and-modeling-with-tidyquant.Rmd b/vignettes/TQ03-scaling-and-modeling-with-tidyquant.Rmd
index 846d75f8..e593072d 100644
--- a/vignettes/TQ03-scaling-and-modeling-with-tidyquant.Rmd
+++ b/vignettes/TQ03-scaling-and-modeling-with-tidyquant.Rmd
@@ -122,7 +122,7 @@ data("FANG")
 FANG
 ```
 
-Second, use `group_by` to group by stock symbol. Third, apply the mutation. We can do this in one easy workflow. The `periodReturns` function is applied to each group of stock prices, and a new data frame was returned with the annual returns in the correct periodicity.
+Second, use `group_by` to group by stock symbol. Third, apply the mutation. We can do this in one easy workflow. The `periodReturn` function is applied to each group of stock prices, and a new data frame was returned with the annual returns in the correct periodicity.
 
 ```{r}
 FANG_returns_yearly <- FANG %>%