1. Hypothesis Tests / 假設檢定
2. Inference About Means and Proportions with Two Populations / 平均數與比例推論
3. Inferences About Population Variances / 兩母體變異數推論
4. Comparing Multiple Proportions, Test of Independence and Goodness of Fit / 比例比較、獨立性與適合度檢定
5. Experimental Design and Analysis of Variance / 實驗設計與變異數分析
6. Simple Linear Regression / 簡單線性迴歸
7. Multiple Regression / 多元線性迴歸
8. Regression Analysis: Model Building / 迴歸分析:模型建立

1. Hypothesis Tests / Assumption Check
2. Inference About Means and Proportions with Two Populations / Average and Proportions
3. Inferences About Population Variances / Recommended for Two-Maternal Variances
4. Comparing Multiple Proportions, Test of Independence and Goodness of Fit / Comparison, Independence and Appropriateness
5. Experimental Design and Analysis of Variance / Experimental Design and Analysis of Variance
6. Simple Linear Regression / Simple Linear Regression
7. Multiple Regression / Multiple Regression
8. Regression Analysis: Model Building / Reflection Analysis: Model Building

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.

Statistics for Business and Economics (13 Edition) by D.R. Anderson, D.J. Sweeney, T. A. Williams, J.D. Camm, J.J. Cochran

Statistics for Business and Economics (13 Edition) by D.R. Anderson, D.J. Sweeney, T. A. Williams, J.D. Camm, J.J. Cochran