In probability and statistics, the variance of a random variable is the average value of the square distance from the mean value. It represents the how the random variable is distributed near the mean value. Sm
All these quantities describe important properties of random variables, although, in general, they do not determine the complete distribution. The expectation of a continuous real-valued random variable can be computed using its density f Y with respect to the Lebesgue measure and the Riemann ...
mean) of the random variable, i.e.[Math Processing Error]Conversely, if a continuous function[Math Processing Error]satisfies[Math Processing Error]for all random variables X, then it is necessarily of the form[Math Processing Error]where a > 0. This also holds in the...
In thousands of dollars: μ = $45,000 σ = $47,000 The mean is now much closer to the most probable value. And the standard deviation is a little smaller (showing that the values are more central.)ContinuousRandom Variables can be either Discrete or Continuous:Discrete...
be acontinuous random variable. Let itssupportbe the set of positive real numbers: Let . We say that has aChi-square distributionwith degrees of freedom if and only if itsprobability density functionis where is a constant: and is theGamma function. ...
be a continuous random variable with support and probability density function Compute its variance. Solution Exercise 6 Read and try to understand how the variance of a Chi-square random variable is derived in the lecture entitledChi-square distribution. ...
Answer to: Determine the mean and the variance for the (continuous) random variables with the following moment-generating function: M(t)=(1-4t)-2...
One final tool is introduced that has practical value in various situations: Winsorized expected values. What will be needed is a generalization of E(X) that maintains standard properties of expected values. Let g(X) be any function of the continuous random variable X. When working with a ...
For continuous variables; it is determined as an area measure. Mathematically expressed in the form of integrals as follows; V(Z)=E(Z2)−(E(Z))2 Answer and Explanation: Given Information The probability density function of random variable X as given in the question is; {eq}f\left...
We use some properties of orthogonal polynomials to provide a class ofupper/lower variance bounds for a function $g(X)$ of an absolutely continuousrandom variable $X$, in terms of the derivatives of $g$ up to some order. Thenew bounds are better than the existing ones....