主要講授推論統計。至少包括：
1. 點估計及區間估計；學會如何運用估計式從資料中萃取資訊，且知道如何判斷估計式的優缺點。
2. 假設檢定；學會如何正確地判讀從資料中萃取的資訊。
3. 迴歸分析；學會如何正確地設定一個迴歸式來釐清資料中各變數之間的關聯性。

Mainly teaches the recommendation statistics. At least include:
1. Point estimates and regional estimates; learn how to use the estimate formula to extract information from the data and know how to judge the advantages and disadvantages of the estimate formula.
2. Assume confirmation; learn how to correctly judge the information extracted from the data.
3. Recitation analysis; learn how to correctly set a recitation to clarify the correlation between variables in the data.

統計方法是現今計量科學研究中最常用的方法之一，但是，隨著科技的進步、套裝軟體的發達，同學可以很容易的處理一些基本資料的分析及推論，但並不全然了解方法背後之理論基礎。因此，本課程的主要目的是建立同學能獲正確的統計基本概念。盡量以簡單、生動且易於了解的方式講授課程內容進而引發同學學習之興趣，避免艱深的內容和太多的數學推導。本課程內容包含：
1. 敘述統計：關於數據資料的描述及整理。
2. 機率論：統計推論的基礎。
3. 假設檢定。
4. 變方分析與實驗設計。
5. 迴歸分析。

Statistical methods are one of the most commonly used methods in today's quantitative scientific research. However, with the advancement of technology and the development of packaged software, students can easily handle the analysis and recommendation of some basic data, but they do not fully understand the theoretical basis behind the method. Therefore, the main purpose of this course is to establish the basic statistical concepts that students can obtain correctly. As much as possible, teach the course content in a simple, vivid and easy to understand way to attract students' interest in learning, avoiding deep content and too much mathematical guidance. The course includes:
1. Statistics: Description and sorting of data.
2. Opportunity theory: the basis of statistical recommendation.
3. Assume confirmation.
4. Change analysis and experimental design.
5. Reply analysis.

1. 管中閔 著，統計學：觀念與方法，華泰。
2. 陳旭昇 著，統計學：應用與進階，東華。

1. Guanzhongguan, scheming: concepts and methods, Huatai.
2. Chen Xusheng, Statistical Technique: Application and Advanced, East China.