| Course Objective |
|
| Course Description |
|
| Course Schedule |
Week
|
Topic
|
Content and Reading Assignment
|
Teaching Activities and Homework
|
1
|
Introduction;
Simple Linear Regression
|
Course Introduction, Chapter 1
|
Lecture
|
2
|
Inferences in Regression Analysis
|
Chapter 2
|
Lecture, HW
|
3
|
Correlation Analysis
|
Chapter 2
|
Lecture
|
4
|
Model Diagnostics (I)
|
Chapter 3
|
Lecture, HW
|
5
|
Remedial Measures
|
Chapter 3
|
Lecture, Quiz
|
6
|
Simultaneous Inferences
|
Chapter 4
|
Lecture
|
7
|
Matrix Approach to Regression
|
Chapter 5
|
Lecture, HW
|
8
|
Data analysis using R or SAS.
|
Chapter 1-5
|
Discussion, E-Learning
|
9
|
Midterm Exam
|
|
|
10
|
Multiple Regression (I)
|
Chapter 6
|
Lecture
|
11
|
Multiple Regression (II)
|
Chapter 7
|
Lecture, HW
|
12
|
Regression Models for Quantitative and Qualitative Predictors
|
Chapter 8
|
Lecture, HW
|
13
|
Model Selection and Validation
|
Chapter 9
|
Lecture, HW
|
14
|
Model Diagnostics (II)
|
Chapter 11
|
Lecture, Quiz
|
15
|
Other Remedial Measures
|
Chapter 11
|
Lecture
|
16
|
Data analysis using R or SAS
|
Chapter 6-11
|
Discussion, E-Learning
|
17
|
Review, Brief Introduction to Logistic/Poisson Regression
|
Chapter 14
|
Lecture
|
18
|
Final Exam
|
|
|
|
| Teaching Methods |
|
| Teaching Assistant |
To be announced.
|
| Requirement/Grading |
Attendance 10%, Quiz 20%, Midterm Exam 35%, Final Exam 35%
|
| Textbook & Reference |
Required Textbook: Michael H. Kutner et al. (2019). Applied Linear Statistical Models: Applied Linear Regression Models (5th edition), Mcgraw-Hill Inc. (華泰文化).
Some References:
- Douglas C. Montgomery, Elizabeth A. Peck, and G. Geoffrey Vining (2021). Introduction to Linear Regression Analysis (6th Edition).
- John Fox and Sanford Weisberg (2018). An R Companion to Applied Regression (3rd Edition), SAGE Publications, Inc.
|
| Urls about Course |
| http://moodle.nccu.edu.tw/ |
| Attachment |
|