Applied Statistics
This course focuses on some fundamental applied statistical knowledge, including basic probability, distributions, estimation problems, hypotheses, sampling methods, (non)linear regression models, nonparametric statistics, and applications in the engineering field. Additionally, it provides a detailed introduction to the application scenarios through specific real-world projects.【Attention: We are hiring two BIMSA/Qiuzhen students (with an extra salary) to join our project with COMAC. Please attend the first class if you're interested. We are trying to use importance sampling and neural networks to solve the sampling problem in the auto-landing system. I will introduce the details in this class. Welcome to JOIN! 】
Lecturer
Date
10th September ~ 10th December, 2024
Location
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| Tuesday | 09:50 - 11:25 | A6-101 | ZOOM B | 462 110 5973 | BIMSA |
Prerequisite
Basic knowledge of probability and statistics
Syllabus
1. Introduction and An Example
2. Probability: random variables and distributions
3. Fundamental Sampling distributions
4. One- and Two-Sample Estimation Problems
5. One- and Two-Sample Tests of Hypotheses
6. Smoothing
7. Monte Carlo Methods
8. Importance Sampling Methods
9. Optimization-1: Linear Regression Models
10. Optimization-2: Nonlinear Regression Models
11. Optimization-3: Expectation Maximization Algorithms
12. Nonparametric Statistics
2. Probability: random variables and distributions
3. Fundamental Sampling distributions
4. One- and Two-Sample Estimation Problems
5. One- and Two-Sample Tests of Hypotheses
6. Smoothing
7. Monte Carlo Methods
8. Importance Sampling Methods
9. Optimization-1: Linear Regression Models
10. Optimization-2: Nonlinear Regression Models
11. Optimization-3: Expectation Maximization Algorithms
12. Nonparametric Statistics
Reference
Ref-1: Probability & Statistics for Engineers & Scientists, Ninth Edition, Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye.
Ref-2: Computational Statistics with R, Niels R. Hansen, https://cswr.nrhstat.org/
Ref-2: Computational Statistics with R, Niels R. Hansen, https://cswr.nrhstat.org/
Audience
Undergraduate
, Advanced Undergraduate
, Graduate
, Postdoc
, Researcher
Video Public
No
Notes Public
Yes
Language
Chinese