| 授業名 | Introduction to BBA Fall |
|---|---|
| Course Title | Introduction to BBA Fall |
| 担当教員 Instructor Name | Xinyang Wei |
| コード Couse Code | NUC422_N23B |
| 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 Term3 |
授業の概要 Course Overview
Misson Statementとの関係性 / Connection to our Mission Statement
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.
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 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.
授業の目的（意義） / Importance of this course
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 such as descriptive statistics and inferential statistics including point and interval estimation of parameters, hypothesis testing and involve case studies, discussions, and interactive activities.
到達目標 / Achievement Goal
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 economic and management problems.
本授業の該当ラーニングゴール Learning Goals
*本学の教育ミッションを具現化する形で設定されています。
LG1 Critical Thinking
LG2 Diversity Awareness
LG3 Ethical Decision Making
LG4 Effective Communication
LG6 Managerial Perspectives (BBA)
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 practical 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.
1. Use fundamental statistics in other courses.
2. Solve statistical problems in an Excel spreadsheet environment.
3. Formulate and solve practical 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 % |
事前学修と事後学修の内容、レポート、課題に対するフィードバック方法 Pre- and Post-Course Learning, 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.
Students should spend no less than 3 hours preparing and reviewing each lecture.
授業スケジュール Course Schedule
第1日（Day1）
Descriptive Statistics - Tables, Graph and Excel Applications●使用するケース
City Delights: A Comprehensive Exploration of Sales Data, Customer Preferences, and Pricing Strategies in Urban Retail (from the instructor)第2日（Day2）
Descriptive Statistics - Numerical Measures and Excel Applications●使用するケース
City Delights: A Comprehensive Exploration of Sales Data, Customer Preferences, and Pricing Strategies in Urban Retail (from the instructor)The Influence of Temperature on Ice Cream Sales - A Quantitative Analysis (from the instructor)
第3日（Day3）
Probability Distributions for Discrete Random VariablesThe Mean and Standard Deviation of a Discrete Random Variable
●使用するケース
Analyzing Daily Order Quantities of a Company (from the instructor)第4日（Day4）
Probability Computations for General Normal Random Variables●使用するケース
Variability in Beverage Canning - A Statistical Analysis (from the instructor)第5日（Day5）
The Central Limit Theorem●使用するケース
Understanding Sample Variability in Grade Point Averages (GPAs) at Prestige College (from the instructor)第6日（Day6）
Large Sample Confidence Interval for a Population Mean●使用するケース
Academic Performance Analysis using GPA as a Metric (from the instructor)第7日（Day7）
Large Sample Hypothesis Tests Concerning a Single Population Mean●使用するケース
Recalibrating the Cosmetics Dispensing Machine: A Statistical Approach to Quality Control (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
*成績は下記該当項目を基に決定されます。
*クラス貢献度合計はコールドコールと授業内での挙手発言の合算値です。
*クラス貢献度合計はコールドコールと授業内での挙手発言の合算値です。
| 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 | 40 % |
| 期末試験 Final Exam | 0 % |
| 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
教科書 Textbook
- Sharpe, DeVeaux and Velleman「Business Statistics」Pearson（2015）0273722166
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
The structure, contents, and assessment will be adjusted based on suggestions from previous participants.
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