3. 강의목표
This course covers the fundamentals of probability theory including probabilistic models, discrete and continuous random variables, limit theorems, and statistical inference. Through this course, students will learn
1. the concepts of probability and random variables;
2. the concepts of limit theorems and Markov chains;
3. the concepts of statistical inference.
4. 강의선수/수강필수사항
The following courses would be helpful, but not pre-required:
- Calculus
- Linear Algebra
5. 성적평가
Midterm exam: 35%
Final exam: 35%
HW: 20%
Attendance: 10%
6. 강의교재
| 도서명 |
저자명 |
출판사 |
출판년도 |
ISBN |
|
Introduction to Probability, 2nd edition
|
D. P. Bertsekas and J. N. Tsitsiklis
|
Athena Scientific
|
2008
|
978-1-886529-23-6
|
7. 참고문헌 및 자료
Peyton Peebles Jr, Probability, Random Variables and Random Signal Principles., 4th INTERNATIONAL Edition
John Schiller, R. Alu Srinivasan, and Murray Spiegel, Schaum's Outline of Probability and Statistics, (4th Edition)
Leon-Garcia, Probability, Statistics, and Random Processes For Electrical Engineering (3rd Edition)
Stark and Woods, Probability and Random Processes with Applications to Signal Processing (3rd Edition)
8. 강의진도계획
1. Sample Space and Probability
2. Discrete Random Variables
3. General Random Variables
4. Further Topics on Random Variables and Expectations
5. The Bernoulli and Poisson Processes
6. Markov Chains
7. Limit Theorems
8. Bayesian Statistical Inference
9. Classical Statistical Inference
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