| Course title | |||||
| 数理統計学 [Mathematical Statistics] | |||||
| Course category | general education courses | Requirement | Credit | 2 | |
| Department | Year | 2～ | Semester | Fall | |
| Course type | Fall | Course code | 01MA0505b | ||
| Instructor(s) | |||||
| 劉 念麟 [] | |||||
| Facility affiliation | Graduate School of Agriculture | Office | Email address | ||
| Course description |
| We aim to understand data analysis using knowledge of statistics, and knowledge of probability is indispensable. In this class, we will be able to use the statistical quantitative analytical skills by acquiring the basic concepts and methods of descriptive statistics and statistical inference, as well as to master the basic probability theory. |
| Expected Learning |
|
(1) The fundamental concepts of probability theory is understood correctly, and capable of its basic calculation. (2) Being able to understand the way of thinking such as presumption and examination from a statistical point of view, and be applicable to actual data. |
| Course schedule |
|
1. Introduction 2. Correlation and General linear model 3. Probability theory 4. Random variable and Distribution function 5. Probability distribution 6. Two-dimensional probability distribution 7. Population and Sample 8. Midterm exam 9. Moment generating function and Characteristic function 10. Law of large numbers and Central limit theorem 11. Sampling distribution and Estimation 12. Interval estimation 13. Hypothesis test 1 14. Hypothesis test 2 15. Final exam |
| Prerequisites |
| It is desirable to be proficient in one-variable and multivariate calculus. |
| Required Text(s) and Materials |
| Distribute prints as necessary. |
| References |
|
服部哲也：理工系の確率・統計入門(学術図書出版社) 藤田岳彦・高岡浩一郎：穴埋め式確率・統計らくらくワークブック(講談社サイエンティフィック) |
| Assessment/Grading |
| Final exam 40%, Midterm exam 30%, exercise in class 30% |
| Message from instructor(s) |
| Course keywords |
| Random variable, Average, Variance, Normal distribution, Sample, Estimate, Hypothesis |
| Office hours |
| Respond to the questions before or after the class, or during the lesson. |
| Remarks 1 |
| Remarks 2 |
| Related URL |
| Lecture Language |
| Japanese |
| Language Subject |
| Last update |
| 9/25/2017 6:47:12 PM |