| 課程與核心能力關聯配比(%) |
課程目標之教學方法與評量方法 |
| 課程目標 |
核心能力 |
配比(%) |
教學方法 |
評量方法 |
| This course develops a solid foundation in probability theory, including combinatorial methods, probability measures, and discrete and continuous random variables. Students will learn conditional probability, expectations, inequalities, and the analysis and transformation of random variables. Emphasis is placed on important probability distributions and their relationships. The course prepares students for further study in Mathematical Statistics I and II. |
| 3.統計分析專業知識 |
| 6.數學、統計、力學之理論解析 |
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| 授課內容(單元名稱與內容、習作/每週授課、考試進度-共16週加自主學習) |
| 週次 |
授課內容 |
| 第1週 |
Combinatorial analysis |
| 第2週 |
Set Theory and the probability set function |
| 第3週 |
Conditional probability and independence |
| 第4週 |
Discrete and continuous random variables |
| 第5週 |
Expectations |
| 第6週 |
Important inequalities |
| 第7週 |
Distributions of two random variables |
| 第8週 |
Conditional distributions and expectations |
| 第9週 |
⭐Midterm Exam (on Thursday, 23 April, 18:30–21:00)⭐
Transformations of univariate and bivariate random variables |
| 第10週 |
Independence and correlation |
| 第11週 |
Transformations for several random variables and extensions |
| 第12週 |
Binomial and Poisson distributions |
| 第13週 |
The gamma, beta, chi-square, and normal distributions |
| 第14週 |
Multivariate normal distributions |
| 第15週 |
⭐Final Exam (on Thursday, 4 June, 18:30–21:00)⭐
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| 第16週 |
Special continuous distributions and mixture distributions |
自主學習
內容 |
02.閱覽產業及學術相關多媒體資料
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| 學習評量方式 |
| Quizzes: 30%, Midterm Exam:35%, Final Exam: 35% |
| 教科書＆參考書目(書名、作者、書局、代理商、說明) |
Hogg, R. V., McKean, J. W., & Craig, A. T. (2019). Introduction to mathematical statistics. 8th Edition, Pearson Education. (華泰文化代理)
Ross, S. M. (2020). A first course in probability. 10th Edition, Pearson Education. (華泰文化代理) |
| 課程教材（教師個人網址請列在本校內之網址） |
| The iLearning site will host the uploaded materials |
| 課程輔導時間 |
| Tuesday 13:00~15:00 |
| 聯合國全球永續發展目標(連結網址) |
| 08.就業與經濟成長 09.工業、創新基礎建設 | 提供體驗課程：N |
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