This course is a continuation of Statistics I. Statistics in Business applies statistical methods in a business context in order to address business related questions and help make evidence based decisions. Students will learn to apply commonly used statistical methods in business contexts and to interpret analyses performed by others.
This course will cover:
1. One-Sample Hypothesis Tests.
2. Two-Sample Hypothesis Tests.
3. Analysis of Variance.
4. Correlation Analysis.
5. Simple Regression.
6. Multiple Regression.
7. Time-Series Analysis
8. Chi-Square Tests and Nonparametric Tests.
9. Statistical analysis on financial data using Microsoft Excel and SAS.

This course is a continuation of Statistics I. Statistics in Business applications statistical methods in a business context in order to address business related questions and help make evidence based decisions. Students will learn to apply commonly used statistical methods in business contexts and to interpret analyzes performed by others.
This course will cover:
1. One-Sample Hypothesis Tests.
2. Two-Sample Hypothesis Tests.
3. Analysis of Variance.
4. Correlation Analysis.
5. Simple Regression.
6. Multiple Regression.
7. Time-Series Analysis
8. Chi-Square Tests and Nonparametric Tests.
9. Statistical analysis on financial data using Microsoft Excel and SAS.

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. Applied Statistics in Business & Economics, 5th Edition, by David P. Doane and Lori E. Seward.
2. Applied Statistics for Business and Management using Microsoft Excel, 2013, Linda Herkenhoff and John Fogli.
3. Statistical Data Analysis Using SAS, 2014, Mervyn G. Marasinghe and Kenneth J. Koehler.

1. Applied Statistics in Business & Economics, 5th Edition, by David P. Doane and Lori E. Seward.
2. Applied Statistics for Business and Management using Microsoft Excel, 2013, Linda Herkenhoff and John Fogli.
3. Statistical Data Analysis Using SAS, 2014, Mervyn G. Marasinghe and Kenneth J. Koehler.