图 书 馆
粒子物理学的统计技术Statistical Techniques for Particle Physics |
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| 课程网址: | http://videolectures.net/cernacademictraining09_cranmer_stpp/ |
| 主讲教师: | Kyle Cranmer |
| 开课单位: | 欧洲核子研究组织 |
| 开课时间: | 2010-09-10 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This series will consist of four 1-hour lectures on statistics for particle physics. The goal will be to build up to techniques meant for dealing with problems of realistic complexity while maintaining a formal approach. I will also try to incorporate usage of common tools like ROOT, RooFit, and the newly developed RooStats framework into the lectures. The first lecture will begin with a review the basic principles of probability, some terminology, and the three main approaches towards statistical inference (Frequentist, Bayesian, and Likelihood-based). I will then outline the statistical basis for multivariate analysis techniques (the Neyman-Pearson lemma) and the motivation for machine learning algorithms. Later, I will extend simple hypothesis testing to the case in which the statistical model has one or many parameters (the Neyman Construction and the Feldman-Cousins technique). From there I will outline techniques to incorporate background uncertainties. If time allows, I will touch on the statistical challenges of searches for physics beyond the standard model and the look-elsewhere effect. |
| 关 键 词: | 粒子物理学; 物理统计学; 统计推理; 概率 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-12-27：lxf |
| 阅读次数: | 29 |