But electoral arithmetic means such a tie-up may have to happen sooner or later.
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When Sanders says the arithmetic means he faces a "steep fight" … well, that's understating things quite a lot.
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Exceptions to the 'average' rule Beyond arithmetic means, some regions -- Alaska, western Canada, South America, parts of the southern portion of Africa, Madagascar, New Zealand, Mexico, eastern Asia, the Atlantic and Indian oceans, and the Bering Sea -- experienced their highest temperatures ever during the first half of the year.
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"Leaving aside the deep mutual mistrust that exists between Renzi and the M5S, the parliamentary arithmetic means that it could become a realistic option only if all the M5S and PD lawmakers support this teaming up between the two parties," Wolfango Piccoli, co-president of global CEO advisory firm Teneo, said in a note Tuesday.
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Data about the (H, 2) sum of To find the (C, 1) Cesàro sum of 1 − 2 + 3 − 4 + ..., if it exists, one needs to compute the arithmetic means of the partial sums of the series. The partial sums are: :1, −1, 2, −2, 3, −3, ..., and the arithmetic means of these partial sums are: :1, 0, , 0, , 0, , .... This sequence of means does not converge, so 1 − 2 + 3 − 4 + ... is not Cesàro summable. There are two well- known generalizations of Cesàro summation: the conceptually simpler of these is the sequence of (H, n) methods for natural numbers n. The (H, 1) sum is Cesàro summation, and higher methods repeat the computation of means.
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Step 4: Calculating the geometric mean of the arithmetic means for each indicator: Obtain the reference standard by aggregating female and male indices with equal weight, and then aggregating indices across dimensions. Reproductive health is not an average of female and male indices but half the distance from the norms established Step 5: Calculating the Gender Inequality Index: To compute the GII compare the equally distributed gender index from Step 3 to the reference standard from Step 4.
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Both Klausen and Schüler as well as Permanyer argue that the GII mixes indices in a few ways which furthers the complexity and poses other issues. The measurement combines well-being and empowerment which becomes problematic in that it increases the complexity, lacks transparency, and suffers from the problem of using an arithmetic means of ratios. Permanyer argues that it also combines two different, absolute and relative, indicators within the same formula. For example, if the MMR is higher than 10 per 100,000 it is considered inequality.
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In mathematical analysis, Cesàro summation (also known as the Cesàro mean ) assigns values to some infinite sums that are not convergent in the usual sense. The Cesàro sum is defined as the limit, as n tends to infinity, of the sequence of arithmetic means of the first n partial sums of the series. This special case of a matrix summability method is named for the Italian analyst Ernesto Cesàro (1859–1906). The term summation can be misleading, as some statements and proofs regarding Cesàro summation can be said to implicate the Eilenberg–Mazur swindle.
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Lynn and Vanhanen base their analysis on selected IQ data from studies which covered 113 nations. For another 79 nations, they estimated the mean IQs on the basis of the arithmetic means of the measured IQs of neighboring countries. They justify this method of estimation by claiming that the correlation between the estimated national IQs they reported in IQ and the Wealth of Nations and the measured national IQs since obtained is very high (0.91). Lynn and Vanhanen calculated the national IQs in relation to a British mean of 100, with a standard deviation of 15.
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Compound annual growth rate (CAGR) is a business and investing specific term for the geometric progression ratio that provides a constant rate of return over the time period. CAGR is not an accounting term, but it is often used to describe some element of the business, for example revenue, units delivered, registered users, etc. CAGR dampens the effect of volatility of periodic returns that can render arithmetic means irrelevant. It is particularly useful to compare growth rates from various data sets of common domain such as revenue growth of companies in the same industry or sector.
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One group consists of pixels in the current block where each pixel's luminance is greater than or equal to the representative luminance for the current block. The second group of pixels consists of pixels in the current block where each pixel's luminance is less than the representative luminance for the current block. Whether a pixel in the current block belongs to a certain group is determined by a binary "0" or a "1" value in another, separate, 16-entry bitmap. ::# Two representative 24-bit colors are now selected for each block of pixels by computing two arithmetic means.
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In industrial statistics, the X-bar chart is a type of Shewhart control chart that is used to monitor the arithmetic means of successive samples of constant size, n. This type of control chart is used for characteristics that can be measured on a continuous scale, such as weight, temperature, thickness etc. For example, one might take a sample of 5 shafts from production every hour, measure the diameter of each, and then plot, for each sample, the average of the five diameter values on the chart. For the purposes of control limit calculation, the sample means are assumed to be normally distributed, an assumption justified by the Central Limit Theorem.
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The weighted arithmetic mean is similar to an ordinary arithmetic mean (the most common type of average), except that instead of each of the data points contributing equally to the final average, some data points contribute more than others. The notion of weighted mean plays a role in descriptive statistics and also occurs in a more general form in several other areas of mathematics. If all the weights are equal, then the weighted mean is the same as the arithmetic mean. While weighted means generally behave in a similar fashion to arithmetic means, they do have a few counterintuitive properties, as captured for instance in Simpson's paradox.
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Consider the sets R and S :R={1, 2, 3, 4} :S={5, 6, 7, 8, 9} The arithmetic mean of R is 2.5, and the arithmetic mean of S is 7. However, if 5 is moved from S to R, producing :R={1, 2, 3, 4, 5} :S={6, 7, 8, 9} then the arithmetic mean of R increases to 3, and the arithmetic mean of S increases to 7.5. Consider this more illustrative example :R={1,2} :S={99, 10,000, 20 000} with arithmetic means 1.5 for R and 10,033 for S. Moving 99 from S to R gives means 34 and 15,000. 99 is orders of magnitude above 1 and 2, and orders of magnitude below 10,000 and 20,000. It should come as no surprise that the transfer of 99 increases the mean of both R and S. The element which is moved does not have to be the very lowest of its set; it merely has to have a value that lies between the means of the two sets. Consider this example: :R={1, 3, 5, 7, 9, 11, 13} (mean = 7) :S={6, 8, 10, 12, 14, 16, 18} (mean = 12) Moving 10, which is larger than R's mean of 7 and smaller than S's mean of 12, from S to R will raise the mean of R from 7 to 7.375, and the mean of S from 12 to 12.333.
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