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One reason why the secretary problem has received so much attention is that the optimal policy for the problem (the stopping rule) is simple and selects the single best candidate about 37% of the time, irrespective of whether there are 100 or 100 million applicants.
In mathematics, the theory of optimal stopping [1] [2] ... Stopping rule problems are associated with two objects: A sequence of random variables ,, ...
37 is a prime number, [1] a sexy prime, and a Padovan prime 37 is the first irregular prime with irregularity index of 1. [2] 37 is the smallest non-supersingular prime in moonshine theory. 37 is also an emirp because it remains prime when its digits are reversed. The secretary problem is also known as the 37% rule, since %.
Wicked problems have no stopping rule. Solutions to wicked problems are not true-or-false, but better or worse. There is no immediate and no ultimate test of a solution to a wicked problem. Every solution to a wicked problem is a "one-shot operation"; because there is no opportunity to learn by trial and error, every attempt counts significantly.
In this regard, analysis by Margaritondo gives an optimal formula of: =, where A is the size of the assembly, P is the population, and E = 0.45±0.03. Applying this formula to the U.S. House of Representatives as of the 2020 Census would give a House of between 379 and 1231 members, while using an exponent of 0.4507 gives 693 (the same result ...
A semi-proportional system that elects multiple winners elected at once with the plurality rule and where each voter casts more than one vote but fewer than the number of seats to fill in a multi-seat district is known as limited voting.
In an increasing system, the time constant is the time for the system's step response to reach 1 − 1 / e ≈ 63.2% of its final (asymptotic) value (say from a step increase). In radioactive decay the time constant is related to the decay constant ( λ ), and it represents both the mean lifetime of a decaying system (such as an atom) before it ...
The assets in financial portfolios are, for practical purposes, continuously divisible while portfolios of projects are "lumpy". For example, while we can compute that the optimal portfolio position for 3 stocks is, say, 44%, 35%, 21%, the optimal position for a project portfolio may not allow us to simply change the amount spent on a project.