From 7f53507c79cdec5feecbc935147e7890da117eb1 Mon Sep 17 00:00:00 2001
From: Lateefah Bello <2019cinnamon@gmail.com>
Date: Tue, 5 Oct 2021 12:02:03 +0100
Subject: [PATCH] fixed spelling error

---
 1-Introduction/01-defining-data-science/README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/1-Introduction/01-defining-data-science/README.md b/1-Introduction/01-defining-data-science/README.md
index ccfe6ef7..aa92a9c9 100644
--- a/1-Introduction/01-defining-data-science/README.md
+++ b/1-Introduction/01-defining-data-science/README.md
@@ -33,7 +33,7 @@ This definition highlights the following important aspects of data science:
 > Another important aspect of Data Science is that it studies how data can be gathered, stored and operated upon using computers. While statistics gives us mathematical foundations, data science applies mathematical concepts to actually draw insights from data.
 
 One of the ways (attributed to [Jim Gray](https://en.wikipedia.org/wiki/Jim_Gray_(computer_scientist))) to look at the data science is to consider it to be a separate paradigm of science:
-* **Empyrical**, in which we rely mostly on observations and results of experiments
+* **Empirical**, in which we rely mostly on observations and results of experiments
 * **Theoretical**, where new concepts emerge from existing scientific knowledge
 * **Computational**, where we discover new principles based on some computational experiments
 * **Data-Driven**, based on discovering relationships and patterns in the data