From 01a5188d74ef5ae54d73d892036e5187a158b396 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=EC=A1=B0=ED=95=B4=EC=B0=BD?=
 <hc.cho@johaechang-ui-MacBookPro-2.local>
Date: Fri, 28 Nov 2025 23:31:40 +0900
Subject: [PATCH] add: overview

---
 book/_toc.yml                           | 3 ++-
 book/prescriptive_analytics/overview.md | 5 +++++
 2 files changed, 7 insertions(+), 1 deletion(-)
 create mode 100644 book/prescriptive_analytics/overview.md

diff --git a/book/_toc.yml b/book/_toc.yml
index 4c35a3e..beb9836 100644
--- a/book/_toc.yml
+++ b/book/_toc.yml
@@ -23,4 +23,5 @@ parts:
       sections:
       - file: cate_and_policy/parametric_cate.ipynb
       - file: cate_and_policy/nonparametric_cate.ipynb
-      - file: cate_and_policy/policy_learning.ipynb
\ No newline at end of file
+      - file: cate_and_policy/policy_learning.ipynb
+    - file: prescriptive_analytics/overview.md
\ No newline at end of file
diff --git a/book/prescriptive_analytics/overview.md b/book/prescriptive_analytics/overview.md
new file mode 100644
index 0000000..8bcc007
--- /dev/null
+++ b/book/prescriptive_analytics/overview.md
@@ -0,0 +1,5 @@
+# Prescriptive Analytics
+
+- Prescriptive Analytics는 데이터를 활용해 최적의 의사결정을 도출하는 분석 방식입니다.  
+- 접근 방식은 크게 **Prediction + Optimization**, **Causal Inference + Optimization** 으로 나눌 수 있습니다.  
+- 이 섹션에서는 **Causal Inference + Optimization** 에 집중하여, 개입의 인과효과(CATE)를 기반으로 **가장 효율적인 정책·전략을 선택하는 방법**을 다룹니다.