SemesterSpring Semester, 2025
DepartmentSophomore Class of Department of Statistics
Course NameRegression Analysis (I)
InstructorCHEN YI-JU
Credit3.0
Course TypeRequired
PrerequisiteStatistics、Statistics (I)、Statistics I、Statistics(Ⅰ)、Statistics(I),Statistic Ⅱ、Statistics、Statistics (II)、Statistics Ⅱ、Statistics II、Statistics(II)orBasic Statistics、Probability and Statistics for Business、Statistics、Statistics and Statistical Computing Language
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

Simple Linear Regression; Inferences in Regression Analysis

Chapters 1 and 2

Lecture, HW

3

Inferences in Regression Analysis; Correlation Analysis

Chapter 2

Lecture, HW

4

Model Diagnostics

Chapter 3

Lecture

5

Model Diagnostics; Remedial Measures

Chapters 1-3

Lecture, HW

6

Remedial Measures

Chapters 1-3

Lecture, HW

7

National Holiday 

 

 

8

Matrix Approach to Regression

Chapter 5

Lecture, HW

9

Midterm Exam

Chapters 1-5

 

10

Multiple Regression (I)

Chapters 6 and 7

Lecture

11

Multiple Regression (I)

Chapters 6 and 7

Lecture, HW

12

Multiple Regression (II)

Chapters 7, 8, and 11

Lecture, HW

13

Model Building (I); Model Selection and Validation

Chapter 9

Lecture, HW

14

Model Diagnostics

Chapter 10

Lecture, HW

15

Model Building (II); Remedial Measures

Chapter 11

Lecture

16

Remedial Measures; Logistic Regression (optional)

Chapters 11 and 14 (optional)

Lecture

17

Final Exam

Chapters 6-11

 

18

Review; Data analysis using R (or SAS)

Chapters 1-11

Discussion, Self-Learning

Teaching Methods
Teaching Assistant

To be announced.


Requirement/Grading

In-Class Attendance and Participation 10%, Homework (Data Analysis) 20%, Midterm Exam 35%, Final Exam 35%



Note: The course schedule and requirements are subject to change based on the actual progress.  (每週教學內容與課程進度，會依實際授課狀況做調整!)


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:




  1. Douglas C. Montgomery, Elizabeth A. Peck, and G. Geoffrey Vining (2021). Introduction to Linear Regression Analysis (6th Edition).

  2. John Fox and Sanford Weisberg (2018). An R Companion to Applied Regression (3rd Edition), SAGE Publications, Inc.


Urls about Course
Moodle: http://moodle.nccu.edu.tw/ ALSM: https://cran.r-project.org/web/packages/ALSM/index.html Note: The course schedule and requirements are subject to change based on the actual progress. (每週教學內容與課程進度，會依實際授課狀況做調整!)
Attachment