This chapter focuses on probability and random variables. To apply probability theory to the process under study in the chapter, it is viewed as a random experiment, that is, as an experiment whose outcome is not known in advance but for which the set of all possible individual outcomes is ...
另可参考Probability and Measure, 3rd Edition by Patrick Billingsley和Feller的卷二. Dudley本人在MIT的本科课18.440 Probability and Random Variables用的是Ross的本科教材,另外Degroot的教材也是本科通用的。 0 有用 白菜 2014-01-01 01:44:44 据说上课的notes很多是借鉴这本书的,课上没有涉及的内容在别处...
整理自MIT的Introduction to Probability and Statistics,分为1)Probability,2)Bayesian Inference,3)Frequentist Inference—Null Hypothesis Significance Testing (NHST),4)Confidence Intervals; Regression四大板块。 一、Probability 1.random variable and distribution Bernoulli(p) Binomial(n,p) Geometric(p) Exponentia...
另可参考Probability and Measure, 3rd Edition by Patrick Billingsley和Feller的卷二. Dudley本人在MIT的本科课18.440 Probability and Random Variables用的是Ross的本科教材,另外Degroot的教材也是本科通用的。 评分☆☆☆ 据说上课的notes很多是借鉴这本书的,课上没有涉及的内容在别处也多少接触过,所以允许我为了...
L05.2 Definition of Random Variables 09:14 L05.3 Probability Mass Functions 10:21 L05.4 Bernoulli & Indicator Random Variables 03:06 L05.5 Uniform Random Variables 04:06 L05.6 Binomial Random Variables 06:08 L05.7 Geometric Random Variables ...
3.1 random variables and discrete distribution 3.2 continuous distributions 3.3 The distributions function 3.4 Bivariate distributions 3.5 marginal distributions 3.6 conditional distributions 3.7 multivariate distributions 3.8 functions of a random variable 3.9 functions of tow or more random variables 3.10 The ...
L09.6 Mixed Random Variablesl09.6混合随机变量 MIT RES.6-012 Introduction to Probability, Spring 2018 View the complete course: https://ocw.mit.edu/RES-6-012S18 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at https://
[229]L23.2 The Sum of Independent Poisson Random Variables.zh_en 04:04 [230]L23.3 Merging Independent Poisson Processes.zh_en 08:22 [231]L23.4 Where is an Arrival of the Merged Process Coming From_.zh_en 05:00 [232]L23.5 The Time Until the First (or last) Lightbulb Burns Out.zh_...
8. Continuous Random Variables8.连续随机变量 MIT 6.041 Probabilistic Systems Analysis and Applied Probability, Fall 2010 View the complete course: http://ocw.mit.edu/6-041F10 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More informatio
Multiple Random Variables Let X and Y denote random variables defined on a sample space Ω. • The joint PMF of X and Y is denoted by pX,Y (x, y ) = P�{X = x} ∩ {Y = y }� • The marginal PMFs of X and Y are given respectively as � pX (x) = ...