diff --git a/01_materials/slides/Classification_II.pdf b/01_materials/slides/Classification_II.pdf
index e2d11445..ea4d11ea 100644
Binary files a/01_materials/slides/Classification_II.pdf and b/01_materials/slides/Classification_II.pdf differ
diff --git a/03_instructional_team/markdown_slides/Classification_II.md b/03_instructional_team/markdown_slides/Classification_II.md
index 380441ef..ccadb25e 100644
--- a/03_instructional_team/markdown_slides/Classification_II.md
+++ b/03_instructional_team/markdown_slides/Classification_II.md
@@ -67,7 +67,7 @@ $$
 **Recall:**  quantifies how many positive observations in the test set were identified as positive 
 
 $$
-\text{Precision} = \frac{\text{Number of correct positive predictions}}{\text{total number of positive test set observations}}
+\text{Recall} = \frac{\text{Number of correct positive predictions}}{\text{total number of positive test set observations}}
 $$
 
 - A good classifier would have high precision and high recall