本課程主要目標是讓學生具備基本統計推理與分析的理論知識與實作能力。課程結束時，學生應能理解並分析政治學期刊中使用的部分統計方法，並能將這些方法應用於自身的研究工作中。課程多數時間將分為兩個部分：理論講授與實作的電腦操作課。

學生的成績將根據以下項目評分：課堂參與與統計軟體操作、三次隨堂測驗、期中及期末報告。

在課程初期，我們將簡要回顧一些基本的數學與統計概念，接著深入探討統計推理的邏輯。課程結束時，學生應能具備以下能力：理解基本統計概念、掌握其應用方式、使用統計方法來檢驗研究假說，並運用基本工具將統計方法實際應用於真實世界的資料分析上。

請注意：由於每班的學習狀況與進度不同，本課程大綱僅為暫定的時間參考。指定閱讀內容可能會提前或延後。此外，我也會不定期建議學生閱讀一些學術期刊文章，這些文章中包含本課程所介紹之統計方法的實際應用範例。將以中文授課。

The main goal of this course is to equip students with theoretical knowledge and practical abilities in basic statistical reasoning and analysis. By the end of the course, students should be able to understand and analyze some of the statistical methods used in political science journals and apply these methods to their own research. Most of the course will be divided into two parts: theoretical lectures and practical computer operation classes.

Students' grades will be graded based on the following items: class participation and operation of statistical software, three in-class tests, and midterm and final reports.

Early in the course, we will briefly review some basic mathematical and statistical concepts, then delve into the logic of statistical reasoning. By the end of the course, students should be able to understand basic statistical concepts, master their applications, use statistical methods to test research hypotheses, and use basic tools to actually apply statistical methods to real-world data analysis.

Please note: Due to the different learning status and progress of each class, this course outline is only a tentative time reference. Assigned readings may be made earlier or later. In addition, I will occasionally recommend students to read some academic journal articles that contain practical application examples of the statistical methods introduced in this course. Classes will be taught in Chinese.

Gujarati, D. N. (2006). Essentials of econometrics (3rd ed.). McGraw-Hill.

Elena Llaudet & Kosuke Imai. (2022). Data Analysis for Social Science: A Friendly and Practical Introduction.

Gujarati, D. N. (2006). Essentials of econometrics (3rd ed.). McGraw-Hill.

Elena Llaudet & Kosuke Imai. (2022). Data Analysis for Social Science: A Friendly and Practical Introduction.