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In this situation, the event A can be analyzed by a conditional probability with respect to B. If the event of interest is A and the event B is known or assumed to have occurred, "the conditional probability of A given B", or "the probability of A under the condition B", is usually written as P(A|B) [2] or occasionally P B (A).
The points (x,y,z) of the sphere x 2 + y 2 + z 2 = 1, satisfying the condition x = 0.5, are a circle y 2 + z 2 = 0.75 of radius on the plane x = 0.5. The inequality y ≤ 0.75 holds on an arc. The length of the arc is 5/6 of the length of the circle, which is why the conditional probability is equal to 5/6.
Given two jointly distributed random variables and , the conditional probability distribution of given is the probability distribution of when is known to be a particular value; in some cases the conditional probabilities may be expressed as functions containing the unspecified value of as a parameter.
The torsion constant or torsion coefficient is a geometrical property of a bar's cross-section. It is involved in the relationship between angle of twist and applied torque along the axis of the bar, for a homogeneous linear elastic bar. The torsion constant, together with material properties and length, describes a bar's torsional stiffness.
Algorithms for calculating variance play a major role in computational statistics.A key difficulty in the design of good algorithms for this problem is that formulas for the variance may involve sums of squares, which can lead to numerical instability as well as to arithmetic overflow when dealing with large values.
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The term "Z-test" is often used to refer specifically to the one-sample location test comparing the mean of a set of measurements to a given constant when the sample variance is known. For example, if the observed data X 1 , ..., X n are (i) independent, (ii) have a common mean μ, and (iii) have a common variance σ 2 , then the sample average ...
Given a discrete random variable X of ordered values to be encoded, let () be the probability for any x in X.Define a function ¯ = < + Algorithm: For each x in X, Let Z be the binary expansion of ¯ ().