シラバス Syllabus

授業名 Business Statistics
Course Title Business Statistics
担当教員 Instructor Name Xinyang Wei
コード Couse Code NUC405_N23A
授業形態 Class Type 講義 Regular course
授業形式 Class Format On Campus
単位 Credits 2
言語 Language EN
科目区分 Course Category 教養教育科目 / Liberal Arts
学位 Degree BBA
開講情報 Terms / Location 2023 UG Nisshin Term2

授業の概要 Course Overview

Statistics involves the gathering, collection, and analysing of data in order to improve decision-making. Statistics is an important field because it enables us to comprehend general trends and patterns in a given data set. Statistics can be used to analyze data and draw conclusions. It can also make predictions about future events and behaviours.

For example, individuals can use statistics to make decisions in financial planning and budgeting, while organizations can be guided by statistics in financial policy decisions. In addition, business practitioners responsible for marketing, management, accounting, sales, or other business functions can also benefit from understanding statistical techniques.

This course provides a statistical foundation for the other courses in the Global BBA program, which educates future innovative and ethical business leaders with a "Frontier Spirit" and creates knowledge that advances modern business and society.
This is a methodology course intended to serve as a foundation for other courses in the global BBA program. The course will cover fundamental statistical tools (descriptive statistics and inferential statistics including point and interval estimation of parameters, hypothesis testing) and involve case studies, discussions, and interactive activities.
Participants will develop an understanding of fundamental methods of statistics in the fields of economics and management and will be able to develop and apply these methods to analyze real-world economic and management problems.

本授業の該当ラーニングゴール Learning Goals


LG1 Critical Thinking
LG2 Diversity Awareness
LG3 Ethical Decision Making
LG4 Effective Communication
LG6 Managerial Perspectives (BBA)

受講後得られる具体的スキルや知識 Learning Outcomes

Students who successfully complete this course will be able to
1. Use fundamental statistics in other courses.
2. Solve statistical problems in an Excel spreadsheet environment.
3. Formulate and solve real-world problems amenable to statistical analysis using data from economics and business, employing methods appropriate to the problem and available data.
4. Develop and strengthen critical and logical thinking as well as problem-solving skills.

SDGsとの関連性 Relevance to Sustainable Development Goals

Goal 4 質の高い教育をみんなに(Quality Education)

教育手法 Teaching Method

教育手法 Teaching Method % of Course Time
インプット型 Traditional 30 %
参加者中心型 Participant-Centered Learning ケースメソッド Case Method 70 %
フィールドメソッド Field Method 0 %
合計 Total 100 %

学習方法、レポート、課題に対するフィードバック方法 Course Approach, Report, Feedback methods

Each lecture is divided into two sections: theory and practice. The theory section helps students establish relevant statistical concepts and explore statistical methods for problem-solving; the practice section requires students to solve practical problems based on the theoretical knowledge they have learned. Active participation in class discussions is expected and required.

Students should spend no less than 3 hours preparing and reviewing each lecture.

授業スケジュール Course Schedule


Descriptive Statistics - Tables, Graph and Numerical Measures

Case discussion: Descriptive Statistics - Tables, Graph and Numerical Measures (from the instructor)


Random Variables and Their Distributions

Case discussion: Random Variables and Their Distributions (from the instructor)


Numerical Characteristics of Random Variables

Case discussion: Numerical Characteristics of Random Variables (from the instructor)


Normal Distribution and T Distribution

Case discussion: Normal Distribution and T Distribution (from the instructor)


Central Limit Theorem

Case discussion: Central Limit Theorem (from the instructor)


Confidence Interval

Case discussion: Confidence Interval (from the instructor)


Hypothesis Testing

Case discussion: Hypothesis Testing (from the instructor)

Note: This is a tentative list, and the teaching content and progress as well as the cases to be used may be adjusted according to the actual situation.

成績評価方法 Evaluation Criteria

講師用内規準拠 Method of Assessment Weights
コールドコール Cold Call 0 %
授業内での挙手発言 Class Contribution 50 %
クラス貢献度合計 Class Contribution Total 50 %
予習レポート Preparation Report 10 %
小テスト Quizzes / Tests 0 %
シミュレーション成績 Simulation 0 %
ケース試験 Case Exam 0 %
最終レポート Final Report 0 %
期末試験 Final Exam 40 %
参加者による相互評価 Peer Assessment 0 %
合計 Total 100 %

評価の留意事項 Notes on Evaluation Criteria

使用ケース一覧 List of Cases


教科書 Textbook

  • Sharpe, DeVeaux and Velleman「Business Statistics」Pearson(2015)

参考文献・資料 Additional Readings and Resource

Notes and case studies will be provided. Textbooks are for reference only.

授業調査に対するコメント Comment on Course Evaluation

This will be the first time the instructor teaches this course at NUCB.

担当教員のプロフィール About the Instructor 

Dr Xinyang Wei is an Associate Professor at NUCB with a PhD in Economics from the University of New South Wales, Sydney. His research delves into intricate aspects of energy and environmental economics, with a focus on policy evaluation, climate change dynamics, and the pursuit of low-carbon development. Recognised for his exemplary research, he was granted the Herbert Smith Freehills Law and Economics Higher Degree Research Award. His scholarly contributions are reflected in publications across renowned academic journals, including Energy Economics, Energy, Renewable Energy, Renewable and Sustainable Energy Reviews, International Journal of Energy Research, and the Journal of Industrial Ecology.

(実務経験 Work experience)

Before joining NUCB, he accumulated enriching teaching and research experiences at both the University of New South Wales and the Macau University of Science and Technology. He possesses a profound background in supervising undergraduate, master's, and PhD theses, and has a versatile teaching portfolio spanning courses like Business Statistics, Data Analysis, Financial Data Analysis, Econometrics, Intermediate Econometrics, Financial Statistics and Econometrics, Financial Risk Management and Research Methodology. His dedication to excellence in education was recognised in Macau with the First Prize in the University Teaching Achievement Award.

Refereed Articles

  • (2023) Study on the spatial spillover effect and path mechanism of green finance development on China's energy structure transformation. Journal of Cleaner Production
  • (2023) Effect of green finance reform and innovation pilot zone on improving environmental pollution: an empirical evidence from Chinese cities. Environmental Science and Pollution Research
  • (2023) The Impact of Fintech Development on Air Pollution. International Journal of Environmental Research and Public Health
  • (2022) Multi-scenario simulation on reducing CO2 emissions from China's major manufacturing industries targeting 2060. Journal of Industrial Ecology
  • (2022) Evaluation of contagious effects of China's wind power industrial policies. Energy