diff --git a/tidy.Rmd b/tidy.Rmd
index f436d17..38db179 100644
--- a/tidy.Rmd
+++ b/tidy.Rmd
@@ -171,7 +171,7 @@ Spreading is the opposite of gathering. You use it when an observation is scatte
 table2
 ```
 
-To tidy this up, we first analysis the representation in similar way to `gather()`. This time, however, we only need two parameters:
+To tidy this up, we first analyse the representation in similar way to `gather()`. This time, however, we only need two parameters:
 
 * The column that contains variable names, the `key` column. Here, it's 
   `type`.
@@ -380,7 +380,7 @@ stocks %>%
 
 `complete()` takes a set of columns, and finds all unique combinations. It then ensures the original dataset contains all those values, filling in explicit `NA`s where necessary.
 
-There's one other important tool that you should know for working with missing values. Sometimes when a data source has primarily been used for data entry, missing values indicate the the previous value should be carried forward:
+There's one other important tool that you should know for working with missing values. Sometimes when a data source has primarily been used for data entry, missing values indicate that the previous value should be carried forward:
 
 ```{r}
 treatment <- frame_data(
@@ -407,7 +407,7 @@ treatment %>%
 
 ## Case Study
 
-To finish off the chapter, let's pull together everything you've learned to tackle a realistic data tidying problem. The `tidyr::who` dataset contains reporter tuberculosis (TB) cases broken down by year, country, age, gender, and diagnosis method. The data comes from the *2014 World Health Organization Global Tuberculosis Report*, available for download at <www.who.int/tb/country/data/download/en/>. 
+To finish off the chapter, let's pull together everything you've learned to tackle a realistic data tidying problem. The `tidyr::who` dataset contains reporter tuberculosis (TB) cases broken down by year, country, age, gender, and diagnosis method. The data comes from the *2014 World Health Organization Global Tuberculosis Report*, available for download at <http://www.who.int/tb/country/data/download/en/>. 
 
 There's a wealth of epidemiological information in this dataset, but it's challenging to work with the data in the form that it's provided: