From e34619c24b613b6df7157ddb14a4451b80a551d8 Mon Sep 17 00:00:00 2001
From: Hunter Greer <137312575+HunterG333@users.noreply.github.com>
Date: Sat, 26 Oct 2024 00:59:51 -0700
Subject: [PATCH] Update 102-big-omega.md (#7587)

Fixed inaccuracy with description
---
 .../103-asymptotic-notation/102-big-omega.md                    | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/data/roadmaps/datastructures-and-algorithms/content/104-algorithmic-complexity/103-asymptotic-notation/102-big-omega.md b/src/data/roadmaps/datastructures-and-algorithms/content/104-algorithmic-complexity/103-asymptotic-notation/102-big-omega.md
index d76cc353d..0b9d5343a 100644
--- a/src/data/roadmaps/datastructures-and-algorithms/content/104-algorithmic-complexity/103-asymptotic-notation/102-big-omega.md
+++ b/src/data/roadmaps/datastructures-and-algorithms/content/104-algorithmic-complexity/103-asymptotic-notation/102-big-omega.md
@@ -1,3 +1,3 @@
 # Big-Ω Notation
 
-The Big Omega (Ω) notation is used in computer science to describe an algorithm's lower bound. Essentially, it provides a worst-case analysis of an algorithm's efficiency, giving us a lower limit of the performance. If we say a function f(n) is Ω(g(n)), it means that from a certain point onwards (n0 for some constant n0), the value of g(n) is a lower bound on f(n). It implies that f(n) is at least as fast as g(n) past a certain threshold. This means that the algorithm won't perform more efficiently than the Ω time complexity suggests.
\ No newline at end of file
+The Big Omega (Ω) notation is used in computer science to describe an algorithm's lower bound. Essentially, it provides a best-case analysis of an algorithm's efficiency, giving us a lower limit of the performance. If we say a function f(n) is Ω(g(n)), it means that from a certain point onwards (n0 for some constant n0), the value of g(n) is a lower bound on f(n). It implies that f(n) is at least as fast as g(n) past a certain threshold. This means that the algorithm won't perform more efficiently than the Ω time complexity suggests.