The field of statistics focuses on quantitative methods that aid in inferring statistical results in a business environment. This course introduces the advanced concepts and methods of statistics with applications in the field of management. Demonstrates methods of presenting data, ANOVA, and Regression. To conceptually understand the basic ideas of statistics, including probability distributions, estimation, hypothesis tests, inferences, experimental design, analysis of variance, regression, etc. Students will also be expected to formulate, solve, and interpret mathematical models from various applications areas in statistics.

The field of statistics focuses on quantitative methods that aid in inferring statistical results in a business environment. This course introduces the advanced concepts and methods of statistics with applications in the field of management. Demonstrates methods of presenting data, ANOVA, and Regression. To conceptually understand the basic ideas of statistics, including probability distributions, estimation, hypothesis tests, inferences, experimental design, analysis of variance, regression, etc. Students will also be expected to formulate, solve, and interpret mathematical models from various applications areas in statistics.

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 inference of some basic data, but they do not fully understand the theoretical basis behind the methods. Therefore, the main purpose of this course is to enable students to acquire correct basic concepts of statistics. Try to teach the course content in a simple, vivid and easy-to-understand way to arouse students' interest in learning, and avoid difficult content and too many mathematical deductions. This course content includes:
1. Narrative statistics: description and organization of data.
2. Probability theory: the basis of statistical inference.
3. Hypothesis test.
4. Variation analysis and experimental design.
5. Regression analysis.

Anderson, Sweeney, Williams, Camm, and Cochran, 2016, Statistics for Business and Economics, 14e, Metric Version, Cengage Learning

Anderson, Sweeney, Williams, Camm, and Cochran, 2016, Statistics for Business and Economics, 14e, Metric Version, Cengage Learning