From 57016461fd2b13d086c6278dde12800887cb88fe Mon Sep 17 00:00:00 2001
From: Chihiro Watanabe <chihiro.watanabe.econ@gmail.com>
Date: Mon, 18 May 2026 15:03:09 +0900
Subject: [PATCH] Update rng usage in lln_clt.md

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---
 lectures/lln_clt.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/lectures/lln_clt.md b/lectures/lln_clt.md
index 476a55482..9ee46a6d6 100644
--- a/lectures/lln_clt.md
+++ b/lectures/lln_clt.md
@@ -562,7 +562,8 @@ NumPy doesn't provide a `bernoulli` function that we can sample from.
 However, we can generate a draw of Bernoulli $X$ using NumPy via
 
 ```python3
-U = np.random.rand()
+rng = np.random.default_rng()
+U = rng.random()
 X = 1 if U < p else 0
 print(X)
 ```