Course Syllabus

Course Information：

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

Fall Semester
Year 2026 362233 Probability 1 3.0 3 ▲ Tofar Chih-Yuan Chang 4EE2A 41 0 　

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2026	362233	Probability	1	3.0	3	▲	Tofar Chih-Yuan Chang	4EE2A	41	0

Course Plan：

Instructor Tofar Chih-Yuan Chang　Office Hours

Email tofar@mail.ntut.edu.tw

Last Updated 2026-06-06 15:51:51

Course Objective 機率空間；組合分析；聯合分佈隨機變數；動差函數及特徵函數；大數法則及中央極限定理。 This course is designed for students to get concepts and methods of Probability and Statistics.

Course Schedule Week 1-4 Sample space and probability - Sets - Probabilistic Models - Conditional Probability - Total Probability Theorem and Bayes’ Rule - Independence - Counting Week 5-9 Discrete random variables - Basic Concepts - Probability Mass Functions - Functions of Random Variables - Expectation, Mean, and Variance - Joint PMFs of Multiple Random Variables - Conditioning - Independence Week 10-15 General Random Variables: - Continuous Random Variables and PDFs - Cumulative Distribution Functions - Normal Random Variables - Joint PDFs of Multiple Random Variables - Conditioning - Independence Week 14-18 Selected further topics (課程內容與授課進度將視實際授課情況與學習狀況滾動式調整)

Evaluation and grading policy Midterm: 35% Final exam: 35% Assignments & Class participation: 30%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
D. P. Bertsekas and J. N. Tsitsiklis, “Introduction to Probability,”2nd Edition, Athena Scientific Inc., 2008

The access to curricular consultation Mon. 13:00–15:00 & Wed. 16:00–18:00, 214B, Integrated Technology Complex Building. (Advance appointment required.)
Students may also contact the instructor by e-mail (tofar@mail.ntut.edu.tw).

Expanding teaching and resources ● 參與式創新教學 (Participatory & Innovative Teaching)
強調學生參與與產出，導入翻轉、PBL/專題、設計思考或遊戲化等策略。
Emphasizes student engagement and outcomes by adopting strategies such as Flipped Classroom, PBL (Problem/Project- Based Learning), Design Thinking, or Gamification.
● 數位科技融入 (Digital Technology Integration)
運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。
Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.

The course corresponds to the SDGs SDG3：良好健康和福祉（Good Health and Well-being）
SDG4：優質教育（Quality Education）
SDG10：減少不平等（Reduced Inequalities）
SDG16：和平正義與有力的制度（Peace, Justice and Strong Institutions）

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	Tofar Chih-Yuan Chang　Office Hours
Email	tofar@mail.ntut.edu.tw
Last Updated	2026-06-06 15:51:51
Course Objective	機率空間；組合分析；聯合分佈隨機變數；動差函數及特徵函數；大數法則及中央極限定理。 This course is designed for students to get concepts and methods of Probability and Statistics.
Course Schedule	Week 1-4 Sample space and probability - Sets - Probabilistic Models - Conditional Probability - Total Probability Theorem and Bayes’ Rule - Independence - Counting Week 5-9 Discrete random variables - Basic Concepts - Probability Mass Functions - Functions of Random Variables - Expectation, Mean, and Variance - Joint PMFs of Multiple Random Variables - Conditioning - Independence Week 10-15 General Random Variables: - Continuous Random Variables and PDFs - Cumulative Distribution Functions - Normal Random Variables - Joint PDFs of Multiple Random Variables - Conditioning - Independence Week 14-18 Selected further topics (課程內容與授課進度將視實際授課情況與學習狀況滾動式調整)
Evaluation and grading policy	Midterm: 35% Final exam: 35% Assignments & Class participation: 30%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes D. P. Bertsekas and J. N. Tsitsiklis, “Introduction to Probability,”2nd Edition, Athena Scientific Inc., 2008
The access to curricular consultation	Mon. 13:00–15:00 & Wed. 16:00–18:00, 214B, Integrated Technology Complex Building. (Advance appointment required.) Students may also contact the instructor by e-mail (tofar@mail.ntut.edu.tw).
Expanding teaching and resources	● 參與式創新教學 (Participatory & Innovative Teaching) 強調學生參與與產出，導入翻轉、PBL/專題、設計思考或遊戲化等策略。 Emphasizes student engagement and outcomes by adopting strategies such as Flipped Classroom, PBL (Problem/Project- Based Learning), Design Thinking, or Gamification. ● 數位科技融入 (Digital Technology Integration) 運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。 Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.
The course corresponds to the SDGs	SDG3：良好健康和福祉（Good Health and Well-being） SDG4：優質教育（Quality Education） SDG10：減少不平等（Reduced Inequalities） SDG16：和平正義與有力的制度（Peace, Justice and Strong Institutions）
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