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Consider the sum, Z, of two independent binomial random variables, X ~ B(m 0, p 0) and Y ~ B(m 1, p 1), where Z = X + Y.Then, the variance of Z is less than or equal to its variance under the assumption that p 0 = p 1 = ¯, that is, if Z had a binomial distribution with the success probability equal to the average of X and Y 's probabilities. [8]
for -measurable , we have ((())) =, i.e. the conditional expectation () is in the sense of the L 2 (P) scalar product the orthogonal projection from to the linear subspace of -measurable functions. (This allows to define and prove the existence of the conditional expectation based on the Hilbert projection theorem .)
Consider any primitive solution (x, y, z) to the equation x n + y n = z n. The terms in (x, y, z) cannot all be even, for then they would not be coprime; they could all be divided by two. If x n and y n are both even, z n would be even, so at least one of x n and y n are odd. The remaining addend is either even or odd; thus, the parities of the ...
Let Y be a random variable and X another random variable on the same probability space. The law of total variance can be understood by noting: The law of total variance can be understood by noting: Var ( Y ∣ X ) {\displaystyle \operatorname {Var} (Y\mid X)} measures how much Y varies around its conditional mean E [ Y ∣ X ...
The proposition in probability theory known as the law of total expectation, [1] the law of iterated expectations [2] (LIE), Adam's law, [3] the tower rule, [4] and the smoothing theorem, [5] among other names, states that if is a random variable whose expected value is defined, and is any random variable on the same probability space, then
A binary equaliser (that is, an equaliser of just two functions) is also called a difference kernel.This may also be denoted DiffKer(f, g), Ker(f, g), or Ker(f − g).The last notation shows where this terminology comes from, and why it is most common in the context of abstract algebra: The difference kernel of f and g is simply the kernel of the difference f − g.
The transform v of u is continuous in a small disc |z| ≤ r and harmonic everywhere in the interior except possibly 0. Let w be the harmonic function given by the Poisson integral on |z| ≤ r with the same boundary value g as v on |z| = r. Applying the maximum principle to v − w + ε log |z| on δ ≤ |z| ≤ r, it must be
For propositional connectives, this is easy; one simply applies the corresponding Boolean operators to the truth values of the subformulae. For example, if φ(x) and ψ(y,z) are formulas with one and two free variables, respectively, and if a, b, c are elements of the model's universe to be substituted for x, y, and z, then the truth value of