| 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. Develop fundamental analytical skills in time-series analyses.
2. Learn how to interpret analytical results.
3. Apply advanced statistical models in business analytics.
|
|
|
| Discussion |
| Lecturing |
| Exercises |
|
| Attendance |
| Quiz |
| Assignment |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Introduction to Forecasting |
| Week 2 |
Exploring Data Patterns and Choosing a Forecasting Technique |
| Week 3 |
Exploring Data Patterns and Choosing a Forecasting Technique |
| Week 4 |
Moving Averages and Smoothing Methods |
| Week 5 |
Moving Averages and Smoothing Methods |
| Week 6 |
Time Series and Their Components |
| Week 7 |
Simple Linear Regression |
| Week 8 |
Holiday |
| Week 9 |
Midterm Exam |
| Week 10 |
Multiple Regression Analysis |
| Week 11 |
Regression with Time Series Data |
| Week 12 |
Regression with Time Series Data |
| Week 13 |
The Box-Jenkins (ARIMA) Methodology |
| Week 14 |
The Box-Jenkins (ARIMA) Methodology |
| Week 15 |
Judgmental Forecasting and Forecast Adjustment |
| Week 16 |
Case 1
Case 2
Presentations |
self-directed
learning |
|
|
| Evaluation |
1. Participation: 20%
2. Examinations: 40%
3. Final Presentation: 40% |
| Textbook & other References |
| Hanke, K. E. & Wichern, D. (2014) Business Forecasting (Ninth Edition) (ISBN: 9781292023007) |
| Teaching Aids & Teacher's Website |
|
| Office Hours |
Tuesday 14:00-16:00
Tel: (04)2284-0392 ext. 764
E-mail: jlu@dragon.nchu.edu.tw; janeluhsu@gmail.com |
| Sustainable Development Goals, SDGs(Link URL) |
| | include experience courses：N |
|