在公共行政訴求循證治理的時代，政策制定需立基於更嚴謹的量化證據，而有效的政策溝通亦需仰賴清晰的數據視覺化呈現。本課程希望培養學生運用量化分析的能力與工具，深入解析各類行政資料，將變數關係、統計模式和數據分佈融入政策分析與研究設計中，從而強化論文的實證基礎與方法論的嚴謹度。

本課程將整合地理資訊工具與相關空間分析概念，作為公共行政量化分析的重要方法之一。透過實際案例分析，如：人口結構、產業韌性、公共投資效益、環境監管或是資源配置不均等案例，學習如何將原始的公共資料轉化為具有統計意義的量化指標，呈現政策的影響程度與實證效益，從而讓決策者與公眾能更客觀理解問題的數據脈絡、識別政策盲點，並優化資源配置。此外，本課程亦會導入自動化分析流程與資料視覺化的實做，讓學生建構以量化證據為基礎的政策溝通文本，提升政策對話的科學性與說服力，回應現代治理對於科學化、精準化管理的迫切需求。

In an era when public administration demands evidence-based governance, policy formulation needs to be based on more rigorous quantitative evidence, and effective policy communication also relies on clear visual presentation of data. This course hopes to cultivate students' ability and tools to use quantitative analysis, deeply analyze various administrative data, and integrate variable relationships, statistical models, and data distribution into policy analysis and research design, thereby strengthening the empirical foundation and methodological rigor of the paper.

This course will integrate geographical information tools and related spatial analysis concepts as one of the important methods of quantitative analysis in public administration. Through actual case analysis, such as cases of population structure, industrial resilience, public investment effectiveness, environmental supervision, or uneven resource allocation, learn how to transform original public data into statistically significant quantitative indicators to present the impact and empirical benefits of policies, so that policymakers and the public can more objectively understand the data context of the problem, identify policy blind spots, and optimize resource allocation. In addition, this course will also introduce the practice of automated analysis processes and data visualization, allowing students to construct policy communication texts based on quantitative evidence, enhance the scientific nature and persuasiveness of policy dialogue, and respond to the urgent need for scientific and precise management in modern governance.

1.蘇明道、蔡博文、朱健銘、鍾明光、林美君 (2022) 地理資訊系統基本原理，臺北：華藝學術出版社。
2.溫在弘 (2015) 空間分析方法與應用:使用ArcGIS Pro與R語言，臺北：雙葉書廊。
3.Chang， Kang-Tsung (2018) Introduction to Geographic Information Systems， 9th edition， New York：McGraw-Hill.

1. Su Mingdao, Cai Bowen, Zhu Jianming, Zhong Mingguang, Lin Meijun (2022) Basic Principles of Geographic Information Systems, Taipei: Huayi Academic Press.
2. Wen Zaihong (2015) Spatial analysis methods and applications: using ArcGIS Pro and R language, Taipei: Shuangye Bookstore.
3.Chang, Kang-Tsung (2018) Introduction to Geographic Information Systems, 9th edition, New York: McGraw-Hill.