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Continuous and discrete variables
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1	Appeared in the Twentieth Conference on Uncertainty in Artificial Intelligence, Banff, Canada, JulySolving Factored MDPs with Continuous and Discrete Variables Carlos Guestrin Berkeley Research Center Add to Reading List Source URL: www.bkveton.com Language: English - Date: 2018-07-29 15:59:46
2	Important Concepts Examples Variables A variable is a quantity that can change. Letters Add to Reading List Source URL: media.pearsoncmg.com Language: English - Date: 2014-01-02 18:19:11 Mathematics Statistics Continuous and discrete variables Variable Expected value Dependent and independent variables Predictive analytics Discrete time and continuous time
3	Chapter 6: Continuous Probability Distributions Chapter 6: Continuous Probability Distributions Chapter 5 dealt with probability distributions arising from discrete random variables. Mostly that chapter focused on the b Add to Reading List Source URL: www.coconino.edu Language: English - Date: 2014-08-21 20:08:48 Probability distribution Random variable Standard deviation Probability Illustration of the central limit theorem Cumulative frequency analysis Statistics Probability and statistics Normal distribution
4	Chapter 6: Continuous Probability Distributions Chapter 5 dealt with probability distributions arising from discrete random variables. Mostly that chapter focused on the binomial experiment. There are many other exper Add to Reading List Source URL: www.coconino.edu Language: English - Date: 2014-08-21 20:08:48 Probability and statistics Probability theory Normal distribution Normal probability plot Standard deviation Standard score Errors and residuals in statistics Standard error Probability distribution Statistics Data analysis Summary statistics
5	Chapter 2. Review of basic Statistical methods 1 Distribution, conditional distribution and moments We consider two kinds of random variables: discrete and continuous random variables. For discrete random variable X, the Add to Reading List Source URL: www.math.mtu.edu Language: English - Date: 2006-09-14 13:48:29 M-estimator Fisher information Expectation–maximization algorithm Likelihood function Probability density function Expected value Random variable Statistics Estimation theory Maximum likelihood
6	Maximum Entropy Inference for Mixed Continuous-Discrete Variables Add to Reading List Source URL: www.fernuni-hagen.de Language: English - Date: 2011-11-29 06:50:37 Statistical theory Information theory Randomness Poisson processes Probability theory Maximum entropy probability distribution Principle of maximum entropy Kullback–Leibler divergence Exponential distribution Statistics Probability and statistics Mathematical analysis