Examples of using Random variables in English and their translations into Czech
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Colloquial
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Official
Random variables?
Mean and variance of random variables.
Random variables and their description.
Correlation and independence of random variables.
Probability and random variables allowance 4/0.
Random variables and their characteristics allowance 0/2.
Characteristics of random variables and their properties.
They get acquainted with basic methods of the determination of possible statistical dependence of two or more random variables.
Operations with random variables, mixture of random variables. .
Review of the basics of probability- random event, random variable, working with random variables.
Importance of some continuous random variables in the economy- exponential and normal distribution?
Random vector: Joint and marginal statistics, correlation coefficient, dependence and independence of random variables.
The importance of some discrete random variables in the economy- Poisson and binomial distribution?
Students are introduced to elements of probability thinking, ability of the synthesis both prior and posterior information anduse to work with random variables.
The importance of some discrete random variables in the economy- Poisson and binomial distribution.
Random variables and their properties, unary and binary operations on random variables, fundamental distributions, random vectors, mixtures of random variables. .
Importance of some continuous random variables in the economy- exponential and normal distribution.
Topics include-- probability, binomial and normal distributions, 2 sample hypothesis tests for means and proportions, applied combinative… something,discrete and continuous random variables, and simple linear regression.
Includes descriptions of probability, random variables and their distributions, characteristics and operations with random variables. .
They will be able to apply correctly basic models of the distribution of random variables and to solve applied probability problems in the area of informatics and computer science.
First classical probability is introduced, then theory of random variables is developed including examples of the most important types of discrete and continuous distributions.
Next chapters contain moment generating functions and moments of random variables, expectation and variance, conditional distributions and correlation and independence of random variables.
Distribution function, density and random variable probability function.
Random variable: Distribution function of a random variable, continuous and discrete distributions, quantiles, median.
Sampling methods, random variable, distribution of random variable allowance 2/4.
Random variable and random vector.
Discrete random variable- distribution function, expected value, variance.
Now this girl, Keri,she's a random variable.
Random variable, random vector- density, distribution function, expected value, variance; examples of discrete and continuous distributions.
Now, in high school,by applying the methodology of statistical probability, accounting for the continuous random variable of luck, I was able to come up with a fairly effective card-counting technique.