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==Examples== ===Location=== Common measures of location, or [[central tendency]], are the [[arithmetic mean]], [[median]], [[mode (statistics)|mode]], and [[interquartile mean]].<ref>{{cite book | last1 = Bullen | first1 = P. S. | date = 2003-08-31 | chapter = | chapter-url = | chapter-url-access = | title = Handbook of Means and Their Inequalities | url = | url-status = | url-access = | format = | type = | series = Mathematics and Its Applications | language = en | volume = 560 | edition = 2 | publisher = [[Springer Science+Business Media|Springer Dordrecht]] | doi = 10.1007/978-94-017-0399-4 | isbn = 978-1-4020-1522-9 | lccn = 2003060794 | oclc = 939214285 | ol = OL8370727M | quote = | quote-page = | quote-pages = | df = dmy-all }}</ref><ref>{{cite book | last1=Grabisch | first1=Michel | last2 = Marichal | first2=Jean-Luc | last3=Mesiar | first3=Radko | last4=Pap | first4=Endre |date=2009 |title=Aggregation Functions |publisher=Oxford University Press | isbn = 978-0521519267 }}</ref> ===Spread=== Common measures of [[statistical dispersion]] are the [[standard deviation]], [[variance]], [[range (statistics)|range]], [[interquartile range]], [[absolute deviation]], [[mean absolute difference]] and the [[distance standard deviation]]. Measures that assess spread in comparison to the typical size of data values include the [[coefficient of variation]]. The [[Gini coefficient]] was originally developed to measure income inequality and is equivalent to one of the [[L-moment]]s. A simple summary of a dataset is sometimes given by quoting particular [[order statistics]] as approximations to selected [[percentiles]] of a distribution. ===Shape=== Common measures of the shape of a distribution are [[skewness]] or [[kurtosis]], while alternatives can be based on [[L-moment]]s. A different measure is the [[Skewness#Distance skewness|distance skewness]], for which a value of zero implies central symmetry. ===Dependence=== The common measure of dependence between paired random variables is the [[Pearson product-moment correlation coefficient]], while a common alternative summary statistic is [[Spearman's rank correlation coefficient]]. A value of zero for the [[distance correlation]] implies independence.
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