Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
Conceptual rather than theoretical understanding of linear and nonlinear regressions. |
|
|
topic Discussion/Production |
Discussion |
Lecturing |
|
Written Presentation |
Oral Presentation |
|
Course Content and Homework/Schedule/Tests Schedule |
Week |
Course Content |
Week 1 |
Review of linear algebra |
Week 2 |
Simple linear regression |
Week 3 |
Simple linear regression |
Week 4 |
Multiple linear regression |
Week 5 |
Basic variable selection |
Week 6 |
Interactions and qualitative predictors |
Week 7 |
ANOVA and ANCOVA |
Week 8 |
Useful transformations |
Week 9 |
presentation 1 |
Week 10 |
Multilevel models |
Week 11 |
Correlated errors |
Week 12 |
Diagnostics |
Week 13 |
High-dimensional problems |
Week 14 |
Global models and local models |
Week 15 |
Prediction models for signal and images |
Week 16 |
presentation 2 |
self-directed learning |
   01.Participation in professional forums, lectures, and corporate sharing sessions related to industry-government-academia-research exchange activities.    02.Viewing multimedia materials related to industry and academia.
|
|
Evaluation |
Reading Assignment: 26%
Presentation 1: 37%
Presentation 2: 37% |
Textbook & other References |
Hadi, A. S., & Chatterjee, S. (2023). Regression analysis by example using R. John Wiley & Sons.
Rawlings, J. O., Pantula, S. G., & Dickey, D. A. (1998). Applied regression analysis: a research tool. New York, NY: Springer New York. |
Teaching Aids & Teacher's Website |
The iLearning site will host the uploaded materials. |
Office Hours |
Tuesday 13:00~15:00 |
Sustainable Development Goals, SDGs(Link URL) |
08.Decent Work and Economic Growth   09.Industry, Innovation and Infrastructure | include experience courses:N |
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