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  2. Expected mean squares - Wikipedia

    en.wikipedia.org/wiki/Expected_mean_squares

    In statistics, expected mean squares (EMS) are the expected values of certain statistics arising in partitions of sums of squares in the analysis of variance (ANOVA). They can be used for ascertaining which statistic should appear in the denominator in an F-test for testing a null hypothesis that a particular effect is absent.

  3. Expected value - Wikipedia

    en.wikipedia.org/wiki/Expected_value

    According to this definition, E[X] exists and is finite if and only if E[X +] and E[X −] are both finite. Due to the formula |X| = X + + X −, this is the case if and only if E|X| is finite, and this is equivalent to the absolute convergence conditions in the definitions above. As such, the present considerations do not define finite ...

  4. Born rule - Wikipedia

    en.wikipedia.org/wiki/Born_rule

    The Born rule is a postulate of quantum mechanics that gives the probability that a measurement of a quantum system will yield a given result. In one commonly used application, it states that the probability density for finding a particle at a given position is proportional to the square of the amplitude of the system's wavefunction at that position.

  5. Law of the unconscious statistician - Wikipedia

    en.wikipedia.org/wiki/Law_of_the_unconscious...

    This proposition is (sometimes) known as the law of the unconscious statistician because of a purported tendency to think of the aforementioned law as the very definition of the expected value of a function g(X) and a random variable X, rather than (more formally) as a consequence of the true definition of expected value. [1]

  6. Variance - Wikipedia

    en.wikipedia.org/wiki/Variance

    In other words, the variance of X is equal to the mean of the square of X minus the square of the mean of X. This equation should not be used for computations using floating point arithmetic , because it suffers from catastrophic cancellation if the two components of the equation are similar in magnitude.

  7. Campbell's theorem (probability) - Wikipedia

    en.wikipedia.org/wiki/Campbell's_theorem...

    In probability theory and statistics, Campbell's theorem or the Campbell–Hardy theorem is either a particular equation or set of results relating to the expectation of a function summed over a point process to an integral involving the mean measure of the point process, which allows for the calculation of expected value and variance of the random sum.

  8. Conditional expectation - Wikipedia

    en.wikipedia.org/wiki/Conditional_expectation

    The unconditional expectation of rainfall for an unspecified day is the average of the rainfall amounts for those 3652 days. The conditional expectation of rainfall for an otherwise unspecified day known to be (conditional on being) in the month of March, is the average of daily rainfall over all 310 days of the ten–year period that fall in ...

  9. Law of total expectation - Wikipedia

    en.wikipedia.org/wiki/Law_of_total_expectation

    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