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The Penrose method (or square-root method) is a method devised in 1946 by Professor Lionel Penrose [1] for allocating the voting weights of delegations (possibly a single representative) in decision-making bodies proportional to the square root of the population represented by this delegation.
With n = 2, the underestimate is about 25%, but for n = 6, the underestimate is only 5%. Gurland and Tripathi (1971) provide a correction and equation for this effect. [ 4 ] Sokal and Rohlf (1981) give an equation of the correction factor for small samples of n < 20. [ 5 ]
Finding the square root of this variance will give the standard deviation of the investment tool in question. Financial time series are known to be non-stationary series, whereas the statistical calculations above, such as standard deviation, apply only to stationary series.
The Pareto principle may apply to fundraising, i.e. 20% of the donors contributing towards 80% of the total. The Pareto principle (also known as the 80/20 rule, the law of the vital few and the principle of factor sparsity [1] [2]) states that for many outcomes, roughly 80% of consequences come from 20% of causes (the "vital few").
Using the nearest-rank method on lists with fewer than 100 distinct values can result in the same value being used for more than one percentile. A percentile calculated using the nearest-rank method will always be a member of the original ordered list. The 100th percentile is defined to be the largest value in the ordered list.
The scoring method used in many sports that are evaluated by a panel of judges is a truncated mean: discard the lowest and the highest scores; calculate the mean value of the remaining scores. [ 10 ] The Libor benchmark interest rate is calculated as a trimmed mean: given 18 responses, the top 4 and bottom 4 are discarded, and the remaining 10 ...
This result is often encountered in social-science and medical-science statistics, [1] [2] [3] and is particularly problematic when frequency data are unduly given causal interpretations. [4] The paradox can be resolved when confounding variables and causal relations are appropriately addressed in the statistical modeling [ 4 ] [ 5 ] (e.g ...
Gottfried Wilhelm Leibniz or Leibnitz [a] (1 July 1646 [O.S. 21 June] – 14 November 1716) was a German polymath active as a mathematician, philosopher, scientist and diplomat who is credited, alongside Sir Isaac Newton, with the creation of calculus in addition to many other branches of mathematics, such as binary arithmetic, and statistics.