Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2026 355221 Probability 1 3.0 3 ▲ HO-TING WU 4CSIE2 0 0 　

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2026	355221	Probability	1	3.0	3	▲	HO-TING WU	4CSIE2	0	0

Course Plan：

Instructor HO-TING WU　Office Hours

Email htwu@ntut.edu.tw

Last Updated 2025-12-09 21:17:47

Course Objective The course of probability considers events that may or may not occur. It provides mathematical and logical models to describe random phenomena occurred in natural science, engineering, and social behaviors. This course is an important branch of applied mathematics. The basic theory and numerous applications will be covered.

Course Schedule Week 1. Introduction to Probability; Counting Principle Week 2. Permutations and Combinations Week 3. Sample Spaces, Event and Axioms of Probability Week 4. Some Propositions; Equally Likely Fundamental Events Week 5. Conditional Probability; Bayes Formula Week 6. Independent Events; Sequential Events Week 7. Midterm 1; Random Variables Week 8. Discrete random Variable, CDF, PMF Week 9. Expectation, Variance, and Well Known Discrete Random Variables. Week 10. Continuous Random Variable and PDF Week 11. Well Known Continuous random Variables Week 12. Function of a Random Variable; Midterm 2 Week 13. Two and Multi Dimensional Random Variables Week 14. (Expectations of) Sums of Random Variables Week 15. Correlation and Covariance; Conditional Expectation Week 16. Inequality, the Law of Large Numbers and Limit Theorems Week 17. Selected Topics (Poisson Process, Markov Chain etc) Week 18. Final Exam

Evaluation and grading policy 1. Homeworks + Class participation 20% 2. Two Mid Term Exams. 50% 3. Final Exam. 30%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Please refer to (https://istudy.ntut.edu.tw/learn/index.php) for course website, announcement and updated information。 Textbook: Ghahramani, “Fundamentals of Probability with Stochastic Processes,” 3rd ed., Pearson, 2005 (or PNIE edition, 2014) , or 4th ed., CRC Press, 2019. Reference Books: 1. S. Ross, “A First Course in Probability”, 7th ed., Pearson Prentice Hall, 2006. 2. Leon-Garcia, “Probability and Random Processes for Electrical Engineering,” 3rd ed., Pearson, 2009. 3. Yates and Goodman, “Probability and Stochastic Processes,” 3rd ed., John Wiley & Sons, 2015. 4. Papoulis and Pillai, “Probability, Random Variables, and Stochastic Processes,” 4th ed., Mc-Graw-Hill, 2002. 5. Walpole, Myers, Myers and Ye, “Probability and Statistics for Engineers and Scientists,” 9th ed., Pearson, 2014.

The access to curricular consultation Welcome to check with me during the office hours or send email in advance to arrange a personal meeting schedule.
Prof. Ho-Ting Wu
Office location: Room# 1528, Technology Building.
(O)(02)27712171 x 4221
email: htwu@ntut.edu.tw

The course corresponds to the SDGs SDG4：優質教育（Quality Education）

Does the course incorporate AI ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）

Note
　

Instructor	HO-TING WU　Office Hours
Email	htwu@ntut.edu.tw
Last Updated	2025-12-09 21:17:47
Course Objective	The course of probability considers events that may or may not occur. It provides mathematical and logical models to describe random phenomena occurred in natural science, engineering, and social behaviors. This course is an important branch of applied mathematics. The basic theory and numerous applications will be covered.
Course Schedule	Week 1. Introduction to Probability; Counting Principle Week 2. Permutations and Combinations Week 3. Sample Spaces, Event and Axioms of Probability Week 4. Some Propositions; Equally Likely Fundamental Events Week 5. Conditional Probability; Bayes Formula Week 6. Independent Events; Sequential Events Week 7. Midterm 1; Random Variables Week 8. Discrete random Variable, CDF, PMF Week 9. Expectation, Variance, and Well Known Discrete Random Variables. Week 10. Continuous Random Variable and PDF Week 11. Well Known Continuous random Variables Week 12. Function of a Random Variable; Midterm 2 Week 13. Two and Multi Dimensional Random Variables Week 14. (Expectations of) Sums of Random Variables Week 15. Correlation and Covariance; Conditional Expectation Week 16. Inequality, the Law of Large Numbers and Limit Theorems Week 17. Selected Topics (Poisson Process, Markov Chain etc) Week 18. Final Exam
Evaluation and grading policy	1. Homeworks + Class participation 20% 2. Two Mid Term Exams. 50% 3. Final Exam. 30%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Please refer to (https://istudy.ntut.edu.tw/learn/index.php) for course website, announcement and updated information。 Textbook: Ghahramani, “Fundamentals of Probability with Stochastic Processes,” 3rd ed., Pearson, 2005 (or PNIE edition, 2014) , or 4th ed., CRC Press, 2019. Reference Books: 1. S. Ross, “A First Course in Probability”, 7th ed., Pearson Prentice Hall, 2006. 2. Leon-Garcia, “Probability and Random Processes for Electrical Engineering,” 3rd ed., Pearson, 2009. 3. Yates and Goodman, “Probability and Stochastic Processes,” 3rd ed., John Wiley & Sons, 2015. 4. Papoulis and Pillai, “Probability, Random Variables, and Stochastic Processes,” 4th ed., Mc-Graw-Hill, 2002. 5. Walpole, Myers, Myers and Ye, “Probability and Statistics for Engineers and Scientists,” 9th ed., Pearson, 2014.
The access to curricular consultation	Welcome to check with me during the office hours or send email in advance to arrange a personal meeting schedule. Prof. Ho-Ting Wu Office location: Room# 1528, Technology Building. (O)(02)27712171 x 4221 email: htwu@ntut.edu.tw
The course corresponds to the SDGs	SDG4：優質教育（Quality Education）
Does the course incorporate AI	● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）
Note