diff --git a/javascript/computer_science/time_complexity.md b/javascript/computer_science/time_complexity.md
index 897cddbbf9..cc01734a03 100644
--- a/javascript/computer_science/time_complexity.md
+++ b/javascript/computer_science/time_complexity.md
@@ -142,7 +142,7 @@ Do the number of steps matter? Yes, they might. We'll touch on when this may be
 
 #### O(log N) - Logarithmic complexity
 
-Logarithmic Complexity tells us that the numbers of steps an algorithm takes increases by 1 as the data doubles. That's still pretty efficient when you think about it. Going from 5,000 to 10,000 data elements and only taking one additional step can scale really well.
+Logarithmic Complexity tells us that the number of steps an algorithm takes increases by 1 as the data doubles. That's still pretty efficient when you think about it. Going from 5,000 to 10,000 data elements and only taking one additional step can scale really well.
 
 One such algorithm that does this is Binary Search. It only works on sorted arrays, but if you have an array of 10 items in sorted order