The second moment of a real random variable is E[X2]. Its variance is E[X2]−(EX)2 when these quantities are finite.
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- Central limit theorem
- Chebyshev's inequality
- Collision-count second moment for independent path weights
- Covariance function
- Covariance matrix
- Half-anisotropic distribution function
- Jensen's inequality
- Kolmogorov maximal inequality
- Kriging
- Law of total variance
- Little's law
- Lyapunov moment inequality
- Ordinary kriging
- Pafnuty Chebyshev
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