統計學
Statistics
| 節 | 週六 |
|---|---|
5 13:20–14:10 | 統計學 M101 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
This course provides a comprehensive introduction to data exploration, probability, and statistical inference, which are essential components of financial analytics. Serving as a foundational course, it aims to equip students with fundamental knowledge and practical implementation skills to address real-world challenges using statistics. To enhance students' abilities in the evolving field of data analytics and capitalize on the positive feedback from previous semesters, this course incorporates training in Python programming for data analysis. Recognizing the importance of practical application, students are required to apply their knowledge through a project component. Selected projects will have the opportunity to be showcased on platforms such as GitHub and YouTube, providing valuable visibility and recognition. By combining theoretical concepts with hands-on programming and project work, this course offers a dynamic and engaging learning experience. Students will gain the necessary skills to leverage statistical techniques for problem-solving in the financial domain while fostering a collaborative and innovative approach to data analytics.
This introductory course in statistics aims to provide a solid foundation for students who are new to the field. With no prerequisites required, this course welcomes beginners with a curious mindset and a belief in statistics as a systematic scientific approach, rather than a mere collection of formulas. While a mathematical background can be advantageous, it is not essential for success in this course.
We use Microsoft Meets for online meetings. TA 黃馨霈
No Item % 1 In-class exercise 20% 2 Prensentation 30% 3 Exam 1 Oct 26 25% 4 Exam 2 Dec 21 25%
| 週次 | 主題 |
|---|---|
| 第 1 週 | No class |
| 第 2 週 | Syllabus, ch 1, 2, 3 |
| 第 3 週 | No class |
| 第 4 週 | Ch 4, 5 |
| 第 5 週 | No class |
| 第 6 週 | ch 7, 8 |
| 第 7 週 | No class |
| 第 8 週 | 7.2, 7.3, 7.5: Sampling distribution and Central limit theorem8.2, 8.3: Point and interval estimation 8.4, 8.5: Large samples, two populations, two proportions9.1, 9.2, 9.3, 9.4, 9.5: Large samples and hypothesis tests |
| 第 9 週 | |
| 第 10 週 | Review and Exam 2 |
| 第 11 週 | |
| 第 12 週 | 10.1, 10.2, 10.5: Small samples, one population12.1, 12.3: Regression, H_0 |
| 第 13 週 | |
| 第 14 週 | 10.3, 10.6, 10.4: small samples for two populations, paired t test12.4, 12.5: Regression, diagnostic tool, CI and PI |
| 第 15 週 | Review and Exam 3 |
| 第 16 週 |
Mendenhall, Beaver, Beaver (2020) Introduction to Probability and Statistics, 15th edition, Cengage Learning, Inc.
- 地點
- Online or M-415
- 時間
- By appointments
- 聯絡方式
- Email: venteng@gmail.com