| 授業名 | Quantitative Analysis |
|---|---|
| Course Title | Quantitative Analysis |
| 担当教員 Instructor Name | Minjeong Ham |
| コード Couse Code | NUC451_N24B |
| 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 |
| 学位 Degree | BBA |
| 開講情報 Terms / Location | 2024 UG Nisshin Term4 |
授業の概要 Course Overview
Misson Statementとの関係性 / Connection to our Mission Statement
This course embodies our school's "frontier spirit" by pushing the boundaries of quantitative analysis in business. It aims to equip students with cutting-edge knowledge and skills necessary to leverage data-driven insights in an ever-evolving business landscape. Students will learn to understand, interpret, and apply advanced quantitative techniques to solve complex business problems, fostering innovation and pioneering approaches in decision-making.
授業の目的（意義） / Importance of this course
In today's data-rich business environment, the ability to analyze and interpret quantitative information is crucial. This course provides students with the tools to make informed, data-driven decisions, enhancing their problem-solving skills and preparing them for leadership roles in various industries.
到達目標 / Achievement Goal
By the end of this course, students will be able to:
○ Apply quantitative analysis techniques to real-world business scenarios.
○ Interpret data sets and draw meaningful conclusions.
○ Develop and evaluate data-driven strategies for business improvement.
○ Apply quantitative analysis techniques to real-world business scenarios.
○ Interpret data sets and draw meaningful conclusions.
○ Develop and evaluate data-driven strategies for business improvement.
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
○ Based on data-driven cases, develop a frontier-minded perspective for AI-driven business transformation
○ Understand the importance of data-driven decision-making in modern business environments
○ Analyze and interpret various data structures and measurements
○ Apply critical thinking to improve analytical models and methods
○ Communicate complex quantitative findings clearly and concisely
○ Understand the importance of data-driven decision-making in modern business environments
○ Analyze and interpret various data structures and measurements
○ Apply critical thinking to improve analytical models and methods
○ Communicate complex quantitative findings clearly and concisely
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 | 25 % | |
| 参加者中心型 Participant-Centered Learning | ケースメソッド Case Method | 75 % |
| 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
○ Students are required to bring a laptop with Microsoft Excel installed to each class.
○ Ensure that the Data Analysis add-in is activated in Excel.
○ Ensure that the Data Analysis add-in is activated in Excel.
授業スケジュール Course Schedule
第1日（Day1）
Importance of data-driven approach 1●使用するケース
Data-Driven Denim: Financial Forecasting at Levi Strauss第2日（Day2）
Importance of data-driven approach 2●使用するケース
Zalora: Data-Driven Pricing Recommendations第3日（Day3）
Background of quantitative analysis●使用するケース
Evaluating Decisions: Correlation or Causation?第4日（Day4）
Strategic improvement based on data-driven decision-making 1●使用するケース
Amazon: Facing Low Customer Satisfaction in Singapore第5日（Day5）
Strategic improvement based on data-driven decision-making 2●使用するケース
Food Truck Forecaster第6日（Day6）
Strategic improvement based on data-driven decision-making 3●使用するケース
GoodBelly: Using Statistics to Justify the Marketing Expense第7日（Day7）
Strategic improvement based on data-driven decision-making 4●使用するケース
Professor Proposes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。
○ Final Report: 30% of total grade (Topic TBA)
○ Final Grade Criteria:
90–100: S
80–89: A
70-79: B
60-69: C
40-59: F-Retry*
Below 40: F
*F-Retry: Students may apply for a make-up opportunity to revise their final report. The student will be assigned a C grade if the revised report scores 60 or above.
○ Academic Integrity Policy: There is zero tolerance for any form of academic dishonesty, including but not limited to Plagiarism, Sharing answers with others, Copying answers or papers, Submitting work done by someone else as one's own
*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 | 70 % |
| クラス貢献度合計 Class Contribution Total | 70 % |
| 予習レポート Preparation Report | 0 % |
| 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 | 30 % |
| 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
○ Class Participation: 70% of total grade (35 for case discussion, 35 for group exercise)○ Final Report: 30% of total grade (Topic TBA)
○ Final Grade Criteria:
90–100: S
80–89: A
70-79: B
60-69: C
40-59: F-Retry*
Below 40: F
*F-Retry: Students may apply for a make-up opportunity to revise their final report. The student will be assigned a C grade if the revised report scores 60 or above.
○ Academic Integrity Policy: There is zero tolerance for any form of academic dishonesty, including but not limited to Plagiarism, Sharing answers with others, Copying answers or papers, Submitting work done by someone else as one's own
教科書 Textbook
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