Expected value

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Expected value

The weighted average of a probability distribution. Also known as the mean value.

Expected Return

The return on an investment as estimated by an asset pricing model. It is calculated by taking the average of the probability distribution of all possible returns. For example, a model might state that an investment has a 10% chance of a 100% return and a 90% chance of a 50% return. The expected return is calculated as:

Expected Return = 0.1(1) + 0.9(0.5) = 0.55 = 55%.

It is important to note that there is no guarantee that the expected rate of return and the actual return will be the same. See also: Abnormal return.
References in periodicals archive ?
Again the expectation values could be interpreted as electron resonance lengths according to equation 6 without the presence of outliers, but some numerical errors remained (results not shown).
Fortunately the high accuracy of the expectation values creates the opportunity to test Muller's model very critically and to extend it.
Tables 2 and 3 show the continued fraction representations when interpreting the expectation values as proton and electron resonances, respectively.
As can be seen, when accepting a small phase shift 6, the radial expectation values can be perfectly interpreted as both, proton and electron resonances.
The equality of the set of partial denominators in the continued fraction representations is a necessary requirement for interpreting the expectation values as both, proton and electron resonances.
So what are the physical arguments for associating the expectation values to both oscillators?
Each run provides two independent z values, one determined by the deviation of the total number of events from its expectation value of 40, the other determined by the deviation of Pot from its expectation value.
For each run, the value of Pot was calculated, and a corresponding z value was derived, using the exact theoretical values for expectation value and variance supplied by Equations 8 and 9.
I selected this plausible measure for its mathematical simplicity, which allows for an explicit calculation of the theoretical expectation value and variance.
Assuming that the events are randomly distributed (with no two events at the same location), the expectation value of Pot in Equation A1 results from N(N - 1) /2 terms which--on average--contribute equally; that is, one can write

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