NCHU Course Outline

Course Name	(中) 商情預測(5552)
Course Name	(Eng.) Business Forecasting
Offering Dept	Continuing Bachelor Program in Innovation Industry Management
Course Type	Elective	Credits	1	Teacher	TSENG LI WEN
Department	Continuing Bachelor Program in Innovation Industry Management(N)Undergraduate	Language	English	Semester	2026-FALL
Course Description	本課程專注於培養學生將市場資料轉化為具預測性與決策價值的分析能力，協助掌握在商業環境中實際面對的預測情境與技術應用。課程內容從需求與銷售預測的核心概念出發，逐步導入移動平均法、指數平滑法、回歸分析、季節性調整與時間序列分解等統計預測方法。透過系統化的教學與操作練習，幫助學生理解模型的運作邏輯與應用情境，並能根據資料特性進行適切的預測技術選擇與執行。課程採用案例導向學習，結合實際商業數據與預測需求設計學習活動，讓學生透過 Excel 建構模型、處理資料與呈現結果，強化操作技能與資料判讀能力。課堂情境涵蓋零售營運、電商平台、產品銷售與市場波動等主題，使學生能將技術操作與商業邏輯整合，進一步提升其策略思考與問題解決能力。在學習歷程中，學生將透過視覺化圖表、簡報製作與分組報告訓練表達預測成果，建立清晰傳達分析結果與建議的能力。課堂亦將鼓勵針對不同產品或產業主題進行小型預測專案設計與討論，引導學生從資料擷取、模型選用到成果呈現發展完整分析流程，培養跨部門協作與專案執行的能力。課程強調實務導向與理論結合，協助學生掌握商情預測在行銷規劃、企劃提案、營運管理與市場研判中的應用價值。完成課程後，學生將能獨立進行預測資料處理與模型建置，具備以數據支持決策的初階實務能力，為日後進入資料分析、行銷科技或數位營運領域奠定基礎。 This course trains students to convert market data into predictive insights for business decision-making. Key topics include demand and sales forecasting using methods such as moving averages, exponential smoothing, regression analysis, seasonal adjustment, and time series decomposition. Through case-based learning and hands-on exercises with Excel, students will model data, interpret results, and communicate findings effectively. Business scenarios cover retail, e-commerce, product sales, and market trends. Students will work on mini-projects involving forecasting tasks across different industries, enhancing their skills in data handling, model selection, and cross-functional collaboration. The course emphasizes practical application, enabling students to build basic forecasting models and support strategic decisions with data—preparing them for roles in analytics, marketing technology, or digital operations.
Prerequisites				self-directed learning in the course	Y

Relevance of Course Objectives and Core Learning Outcomes(%)

Teaching and Assessment Methods for Course Objectives

Course Objectives

Competency Indicators

Ratio(%)

Teaching Methods

Assessment Methods

1.理解商業預測的基本概念與應用情境
2.熟練運用 Excel 建構移動平均、指數平滑與回歸等預測模型
3.解讀趨勢、季節性與需求變化，並進行資料整理與視覺呈現
4.培養從市場資料中辨識問題與提出預測解決策略的能力
5.強化以預測結果支援行銷、企劃與營運決策的實務判斷力

1.Understand core concepts and applications of business forecasting.
2.Build forecasting models using Excel, including moving averages, exponential smoothing, and regression.
3.Interpret trends, seasonality, and demand shifts, and present data through clear visualizations.
4.Identify problems from market data and propose forecasting-based solutions.
5.Apply forecasting re-sults to support mar-keting, planning, and operational decisions with practical judg-ment.

topic Discussion/Production

Discussion

Lecturing

Written Presentation

Attendance

Assignment

Course Content and Homework/Schedule/Tests Schedule

Week	Course Content
Week 1	介紹商情預測的概念 Introduction to Business Forecasting Concepts
Week 2	導論 Introduction
Week 3	變數特性的統計 Statistical Characteristics of Variables
Week 4	變數關係的分析 Analysis of Variable Relationships
Week 5	迴歸分析原理：單變數迴歸 Principles of Regression Analysis: Univariate Regression
Week 6	迴歸分析原理：多變數迴歸 Principles of Regression Analysis: Multivariate Regression
Week 7	因果關係模型 Causal Relationship Models
Week 8	期中報告進度 Midterm Report Progress
Week 9	時間分解模型 Time Decomposition Models
Week 10	時間數列模型：簡易預測法 Time Series Models: Basic Forecasting Methods
Week 11	時間數列模型：ARIMA法 Time Series Models: ARIMA Method
Week 12	無時序因果關係模型個案研究 Case Study: Non-Time-Series Causal Relationship Models
Week 13	時序因果關係模型個案研究 Case Study: Time-Series Causal Relationship Models
Week 14	時間分解模型個案研究 Case Study: Time Decomposition Models
Week 15	時間數列模型個案研究 Case Study: Time Series Models
Week 16	期末報告 Final Report
self-directed learning	03.Preparing presentations or reports related to industry and academia.

Evaluation

出席率 30% Attendance Rate: 30%
課堂討論 20% Classroom Discussion: 20%
期末考試 50% Final Examination: 50%
補救措施： Remedial Measures
證照加分項 Bonus Points for Certifications
期末報告 Final Report

Textbook & other References

教科書 Textbooks
1.用Excel學商業預測—終身受用的原理與實作，葉怡成，博碩文化，2017年8月。
2.資料探勘—程序與模式(使用Excel實作)，葉怡成，五南圖書， 2020年9月。

※請同學採用合法授權用書，並請遵守智慧財產權及性別平等意識，不得非法影印他人著作。

參考書目 References
1.Business Forecasting 9E，John E. Hanke, Dean Wichern，Pearson Education，2014。
2.商業資料分析與應用，洪維廷、彭艷婷、黃國男，全華圖書，二版，2024年2月。
3.Excel 統計分析實務—市場調查與資料分析，楊世瑩，碁峯資訊，2019年11月。
4.問卷資料分析—破解SPSS的六類分析思路，周俊，博碩文化，初版，2018年3月。
5.圖解式統計學與EXCEL，趙元和，五南圖書，初版，2016年9月。

Textbooks
1.Yeh, Y.-C. (2017). Business Forecasting with Excel: Principles and Practices for Lifelong Application. Po-Shuo Publishing.
2.Yeh, Y.-C. (2020). Data Mining: Processes and Patterns (Excel-Based Practice). Wu-Nan Book Inc.

References
1.Hanke, J. E., & Wichern, D. (2014). Business Forecasting (9th ed.). Pearson Education.
2.Hung, W.-T., Peng, Y.-T., & Huang, K.-N. (2024). Business Data Analysis and Applications (2nd ed.). Chuan Hwa Book Co.
3.Yang, S.-Y. (2019). Practical Statistical Analysis with Excel: Market Research and Data Analysis. GOTOP.
4.Chou, C. (2018). Survey Data Analysis: Six Analytical Approaches Using SPSS (1st ed.). Po-Shuo Publishing.
5.Chao, Y.-H. (2016). Illustrated Statistics with Excel (1st ed.). Wu-Nan Book Inc.

Teaching Aids & Teacher's Website

Office Hours

週四 18:00~20:00

Sustainable Development Goals, SDGs(Link URL)

include experience courses：N

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Update Date, year/month/day：2026/07/31 21:28:02	Printed Date, year/month/day：2026 / 8 / 18
The second-hand book website：http://www.myub.com.tw/