3. 강의목표
The course will cover statistical models that describe the data generation process, statistical estimation of the model parameter, and statistical inference. Topics include various estimation, interval estimation, hypothesis testing procedures, and asymptotic theory.
4. 강의선수/수강필수사항
MATH 230 Probability and Statistics
5. 성적평가
| 중간고사 |
기말고사 |
출석 |
과제 |
프로젝트 |
발표/토론 |
실험/실습 |
퀴즈 |
기타 |
계 |
| 30 |
40 |
30 |
|
|
|
|
|
|
100 |
| 비고 |
30 % HW; 70% Exams (Midterm, Final)
The higher exam grade will be 40%. The lower exam grade will be 30%.
There will be 10 homework assignments. Homework will be posted on PLMS course website. A subset of homework problems may be selected for grading. Two lowest scores (including missed ones) will be dropped. "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 |
|
Statistical Inference, 2nd edition
|
G. Casella and R. Berger
|
Duxbury Press
|
2002
|
0534243126
|
8. 강의진도계획
Week 1. Ch 1-2. Basic probability theory
Week 2-5. Ch 5. Properties of a random sample
Week 6-7. Ch 6. Sufficiency
Midterm on Oct 27th, Tuesday
Week 9-11. Ch 7. Point estimation
Week 12-13. Ch 8. Hypothesis testing
Week 14. Ch 9. Interval estimation
Week 15. Ch 10. Asymptotics
Final on Dec 22nd, Tuesday
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