Examples of using Random variables in English and their translations into Chinese
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Political
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Ecclesiastic
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Programming
We have Bernoulli random variables.
Random variables and their distribution 3.
Sum of n independent random variables.
If random variables are independent then.
In this section we treat independence of random variables.
(If the random variables are independent).
Functions of several random variables.
Use when random variables are greater than 0.
In this section, we will focus on continuous random variables(crv).
Many real-world random variables are distributed normally.
Stochastic optimization(SO)methods are optimization methods that generate and use random variables.
Uncorrelated random variables are not necessarily independent.
A Markov chain is a sequence of random variables X 1, X 2, X 3,….
Note that not all random variables have a standard deviation, since these expected values need not exist.
By testing a variety of possibilities, you can understand how random variables could affect your plans and projects.
In particular, some estimators such as Bernoulli NaiveBayes explicitly model discrete boolean random variables.
The generalization of exchangeable random variables is often sufficient and more easily met.
In particular, some estimators such as Bernoulli NaiveBayes explicitly model discrete boolean random variables.
It also helps you understand how random variables could affect your plans and projects.
In particular, some estimators such as Bernoulli NaiveBayes explicitly model discrete boolean random variables.
The proposition that if two random variables have a covariance of 0 they are independent, is not true.
The noncentral distributions(t, F, and chi-square)can be derived from samples of normal random variables with a nonzero mean.
e. the proposition that if two random variables have a covariance of 0 they must be independent, is not true.
In mathematics, a stochastic approach is one in which values areobtained from a corresponding sequence of jointly distributed random variables.
Topics in probability, random variables and stochastic processes applied to the fields of electrical and computer engineering.
Correlation(Correlatio the Latin means"relationship, the relationship")-a definite statistical relationship between two or more random variables.
The main ideais to consider that unknown parameters are random variables, just like the variables describing the experiment.
The first part of the book begins with basic probability, random variables, probability distributions, expectation, correlation and ends with worked questions on special probability distributions.
It is always possible to remove the correlation between zero-méan random variables with a linéar transform, even if the relationship between the variables is nonlinéar.