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So if you assessing income inequality of two countries with different … Therefore the variance is: 1/ (11 - 1) * (1212 - 110 2 /11) = 0.
#Weighted standard deviation r function series
The series or groups of data for which the C.
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What is the advantage of reporting CV? The only advantage is that it lets you compare the scatter of variables expressed in different units. none The coefficient of variance (CV) is the ratio of the standard deviation to the mean (average). _ The coefficient of variation (CV) is a unit less measure typically used to evaluate the variability of a population relative to its standard deviation and is normally presented as a percentage. 56-67.Variance and coefficient of variation 35 \text\)), not only to differentiate it from a one-sample coefficient of variation but also to reflect the fact that in scientific studies you are measuring the variation of repeated measurements on one subject. In: International Journal of Business and Economic Development, 3, 3, p.
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(2015): “Real Economic Convergence in Western Europe from 1995 to 2013”. In: Social Indicators Research, 15, 3, p. (1984): “The Coefficient of Variation: Weighting Considerations”. (2009): “Measuring Regional Inequality: A Comparison of Coefficient of Variation and Hoover Concentration Index”.
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(2005): “Regionale Disparitaeten in Deutschland und ausgesuchten OECD-Staaten im Vergleich”. (eds.): Handbook of Regional Growth and Development Theories. (2009): “Introduction: regional growth and development theories in the twenty-first century - recent theoretical advances and future challenges”. Stuttgart: Borntraeger.Ĭapello, R./Nijkamp, P. Band 1: Univariate und bivariate Statistik”. (2010): “Statistische Methoden in der Geographie. Referencesīahrenberg, G./Giese, E./Mevenkamp, N./Nipper, J. The vector x is automatically treated as a sample (such as in the base sd function), so the denominator of variance is \(n-1\), if it is not, set is.sample = FALSE. As there is more than one way to weight measures of statistical dispersion, this function uses the formula for the weighted sd (\(\sigma_w\)) from Sheret (1984). The standard deviation can be weighted by using a second weighting vector. density of physicians or grocery stores). But the sd can also be used for any other types of disparities or dispersion, such as disparities in supply (e.g. The coefficient of variation (see the function cv) is more frequently used for this purpose (e.g. disparities in regional GDP per capita) in one indicator. The sd allows to summarize regional disparities (e.g. Unlike the R base sd function, the sd2 function allows to choose if the data is treated as sample (denominator of variance is \(n-1\))) or not (denominator of variance is \(n\)))įrom a regional economic perspective, the sd is closely linked to the concept of sigma convergence (\(\sigma\)) which means a harmonization of regional economic output or income over time, while the other type of convergence, beta convergence (\(\beta\)), means a decline of dispersion because poor regions have a stronger growth than rich regions (Capello/Nijkamp 2009). The function calculates the standard deviation. If weighting is specified, the function returns a weighted standard deviation (optionally using a weighted arithmetic mean if wmean = TRUE). Logical argument that whether NA values should be extracted or not Value