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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.
In general, if an increase of x percent is followed by a decrease of x percent, and the initial amount was p, the final amount is p (1 + 0.01 x)(1 − 0.01 x) = p (1 − (0.01 x) 2); hence the net change is an overall decrease by x percent of x percent (the square of the original percent change when expressed as a decimal number).
Each uses one of a variety of methods of allocating seats – the D'Hondt method, the Sainte-Laguë method or a different one. Through the late 1800s and early 1900s, political reformers were involved in discussion and squabbles on the alternative system that would replace the first-past-the-post or block voting systems that were being used.
The average rate for shorter 15-year terms is 6.30% for purchase and 6.30% for refinance, up 5 basis points from 6.25% for purchase and 4 basis points 6.26% for refinance this time last week.
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.
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 ]
These can be distinguished as THD F (for "fundamental"), and THD R (for "root mean square"). [12] [13] THD R cannot exceed 100%. At low distortion levels, the difference between the two calculation methods is negligible. For instance, a signal with THD F of 10% has a very similar THD R of 9.95%. However, at higher distortion levels the ...
The combined "Bing Powered" U.S. searches declined from 26.5% in 2011 to 25.9% in April 2012. [95] By November 2015, its market share had declined further to 20.9%. [ 96 ] As of October 2018, Bing was the third-largest search engine in the US, with a query volume of 4.58%, behind Google (77%) and Baidu (14.45%).