diff --git a/lessons/spatial-complexity.md b/lessons/spatial-complexity.md
index 750c111..5961d03 100644
--- a/lessons/spatial-complexity.md
+++ b/lessons/spatial-complexity.md
@@ -12,7 +12,7 @@ So far we've just talked about _computational complexity_. In general if someone
 
 Let's say we have an algorithm that for every item in the array, it needs to create another array in the process of sorting it. So for an array of length 10, our algorithm will create 10 arrays. For an array of 100, it'd create 100 extra arrays (or something close, remember these are broad strokes, not exact.) This would be O(n) in terms of its spatial complexity. We'll do some sorts that do this.
 
-## Logrithmic
+## Logarithmic
 
 What about another for every item in the array, it needed to create a diminishing amount of extra arrays. For example: for an array of length 10, it'd create 7 arrays. For an array of 100, it'd create 12 arrays. For an array of 1000, it'd created 20 arrays. This would be O(log n).