Discrete Random Variables Discrete Random Variables
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Lecture 1: Entropy and mutual information
www.ece.tufts.eduSimilarly to the discrete case we can define entropic quantities for continuous random variables. Definition The differential entropy of a continuous random variable X with p.d.f f(x) is h(X) = − Z f(x)logf(x)dx = −E[ log(f(x)) ] (15) Definition Consider a pair of continuous random variable (X,Y) distributed according to the joint p.d.f ...
3.1 Concept of a Random Variable
www.d.umn.eduT is a random variable. Discrete Random Variable If a sample space contains a finite number of possibil-ities or an unending sequence with as many elements as there are whole numbers (countable), it is called a discrete sample space. A random variable is called a discrete random variable if its set of possible outcomes is countable.
Classification and regression trees
pages.stat.wisc.eduduce ensemble models using bagging16 and random forest17 techniques. Table 1 summarizes the features of the algorithms. To see how the algorithms perform in a real ap-plication, we apply them to a data set on new cars for the 1993 model year.18 There are 93 cars and 25 variables. We let the Y variable be the type of drive
Techniques for finding the distribution of a transformation ...
www2.econ.iastate.eduDiscrete examples of the method of transformations. 3.1.1. One-to-one function. Find a formula for the probability distribution of the total number of heads obtained in four tossesof a coin where the probability of a head is 0.60. The samplespace, probabilities and the value of the random variable are given in table 1.
Random Variables, Distributions, and Expected Value
www0.gsb.columbia.eduExpectations of Random Variables 1. The expected value of a random variable is denoted by E[X]. The expected value can bethought of as the“average” value attained by therandomvariable; in fact, the expected value of a random variable is also called its mean, in which case we use the notationµ X.(µ istheGreeklettermu.) 2.