3. 강의목표
The course will cover the theory of linear models and generalized linear models. Topics include random vectors, multivariate normal distribution, distributions of quadratic forms, general linear models for normal data, extension to generalized linear models for non-normal data and count data; point and interval estimation; and hypothesis testing.
4. 강의선수/수강필수사항
Required Prerequisite: MATH 230 확률 및 통계 (Probability and Statistics)
Suggested Prerequisite : MATH 203 응용선형대수 (Applied Linear Algebra), MATH 530 수리통계학 (Mathematical Statistics)
5. 성적평가
30 % HW; 70% Exams (Midterm, Final)
The higher exam grade will be 40%. The lower exam grade will be 30%.
There will be 6 homework assignments. Homework will be posted on PLMS course website. "Late HW will receive a grade of zero."
The passing grades for students who choose the S/U grading option are B0 or higher.
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
|
Linear Regression Analysis
|
George A. F. Seber, Alan J. Lee
|
Wiley
|
2003
|
9780471415404
|
7. 참고문헌 및 자료
Generalized Linear Models, 2nd edition by P. McCullagh and J.A. Nelder.
8. 강의진도계획
Week 1-2: Chapter 1
Week 3-4: Chapter 2
Week 5-8: Chapter 3
Week 8: Midterm
Week 9: Chapter 3
Week 10-11: Chapter 4
Week 12-13: Chapter 5
Week 14-15: Chapter 6
Week 16: Final exam
10. 학습법 소개 및 기타사항
A high level of diligence, responsibility, and academic honesty is expected.
11. 장애학생에 대한 학습지원 사항
- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등
- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등
- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청