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The variance of the random variable resulting from an algebraic operation between random variables can be calculated using the following set of rules: Addition : V a r [ Z ] = V a r [ X + Y ] = V a r [ X ] + 2 C o v [ X , Y ] + V a r [ Y ] {\displaystyle \mathrm {Var} [Z]=\mathrm {Var} [X+Y]=\mathrm {Var} [X]+2\mathrm {Cov} [X,Y]+\mathrm {Var ...
Bernoulli's equation; Bogoliubov–Born–Green–Kirkwood–Yvon hierarchy of equations; Bessel's differential equation; Boltzmann equation; Borda–Carnot equation; Burgers' equation; Darcy–Weisbach equation; Dirac equation. Dirac equation in the algebra of physical space; Dirac–Kähler equation; Doppler equations; Drake equation (aka ...
Wald's equation can be transferred to R d-valued random variables (X n) n∈ by applying the one-dimensional version to every component. If ( X n ) n ∈ N {\displaystyle \mathbb {N} } are Bochner-integrable random variables taking values in a Banach space , then the general proof above can be adjusted accordingly.
The formula in the definition of characteristic function allows us to compute φ when we know the distribution function F (or density f). If, on the other hand, we know the characteristic function φ and want to find the corresponding distribution function, then one of the following inversion theorems can be used. Theorem.
A random variable (also called random quantity, aleatory variable, or stochastic variable) is a mathematical formalization of a quantity or object which depends on random events. [1] The term 'random variable' in its mathematical definition refers to neither randomness nor variability [ 2 ] but instead is a mathematical function in which
Random variables are usually written in upper case Roman letters, such as or and so on. Random variables, in this context, usually refer to something in words, such as "the height of a subject" for a continuous variable, or "the number of cars in the school car park" for a discrete variable, or "the colour of the next bicycle" for a categorical variable.