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6.041 概率系统分析与应用概率(MIT)

6.041 Probabilistic Systems Analysis and Applied Probability (MIT)
课程网址: http://ocw.mit.edu/courses/electrical-engineering-and-computer-sc...  
主讲教师: John Tsitsiklis
开课单位: 麻省理工学院
开课时间: 2010-07-15
课程语种: 英语
中文简介:
欢迎来到6.041/6.431,这是一个关于随机现象和过程的建模和分析的主题,包括统计推断的基础。如今,人们普遍认为概率思维能力是科学素养的一个基本组成部分。例如:《金融时报》认为统计显著性(在本课程结束时将涉及到)的概念是“每个人都应该知道的关于科学的十件事”之一。《科学美国人》(Scientific American)最近的一篇文章认为,统计素养在做出与健康相关的决定时至关重要。最后,《纽约时报》(New York Times)的一篇文章指出,统计数据分析是一个即将到来的职业,从谷歌和Netflix,到管理与预算办公室(Office of Management and Budget),都是有价值的。本课程旨在将数学与概念理解和直觉相结合,介绍相关的模型、技能和工具。
课程简介: Welcome to 6.041/6.431, a subject on the modeling and analysis of random phenomena and processes, including the basics of statistical inference. Nowadays, there is broad consensus that the ability to think probabilistically is a fundamental component of scientific literacy. For example: The concept of statistical significance (to be touched upon at the end of this course) is considered by the Financial Times as one of "The Ten Things Everyone Should Know About Science". A recent Scientific American article argues that statistical literacy is crucial in making health-related decisions. Finally, an article in the New York Times identifies statistical data analysis as an upcoming profession, valuable everywhere, from Google and Netflix to the Office of Management and Budget. The aim of this class is to introduce the relevant models, skills, and tools, by combining mathematics with conceptual understanding and intuition.
关 键 词: 概率; 概率模型; 贝叶斯准则; 离散随机变量; 连续随机变量; 伯努利过程; 泊松过程; 马尔可夫链; 中心极限定理; 统计推断
课程来源: 麻省理工学院公开课
最后编审: 2020-05-31:王勇彬(课程编辑志愿者)
阅读次数: 564