Difference between revisions of "Inter-quantile width"
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''inter-quantile distance, inter-quantile range'' | ''inter-quantile distance, inter-quantile range'' | ||
− | The difference between the lower and upper quantiles of the same level (cf. [[Quantile|Quantile]]). Let | + | The difference between the lower and upper quantiles of the same level (cf. [[Quantile|Quantile]]). Let $F(x)$ be a strictly-monotone continuous distribution function and let $p$ be an arbitrary number, $0<p<1/2$. The inter-quantile distance at level $p$ is defined as $x_{1-p}-x_p$, where $x_p$ and $x_{1-p}$ are the solutions of $F(x_p)=p$ and $F(x_{1-p})=1-p$, respectively. Inter-quantile distances at well-chosen levels $p$ are used in mathematical statistics and probability theory to characterize the dispersion (scatter) of probability distributions. E.g., the difference $x_{0.75}-x_{0.25}$, corresponding to $p=0.25$, has the name inter-quartile distance, and in the case of a normal distribution it is equal to $1.349\sigma$ (where $\sigma$ is the natural measure of dispersion, called the [[Standard deviation|standard deviation]]); half the inter-quartile (inter-decile) is called the [[Probable deviation|probable deviation]] (probable error or semi-inter-quartile distance). If $p=1/6$ or $p=1/10$, the inter-quantile distance is called the inter-sixtile or inter-tentile, respectively. |
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<table><TR><TD valign="top">[1]</TD> <TD valign="top"> G.U. Yale, "An introduction to the theory of statistics" , Griffin (1916)</TD></TR></table> | <table><TR><TD valign="top">[1]</TD> <TD valign="top"> G.U. Yale, "An introduction to the theory of statistics" , Griffin (1916)</TD></TR></table> | ||
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Latest revision as of 21:50, 9 November 2014
inter-quantile distance, inter-quantile range
The difference between the lower and upper quantiles of the same level (cf. Quantile). Let $F(x)$ be a strictly-monotone continuous distribution function and let $p$ be an arbitrary number, $0<p<1/2$. The inter-quantile distance at level $p$ is defined as $x_{1-p}-x_p$, where $x_p$ and $x_{1-p}$ are the solutions of $F(x_p)=p$ and $F(x_{1-p})=1-p$, respectively. Inter-quantile distances at well-chosen levels $p$ are used in mathematical statistics and probability theory to characterize the dispersion (scatter) of probability distributions. E.g., the difference $x_{0.75}-x_{0.25}$, corresponding to $p=0.25$, has the name inter-quartile distance, and in the case of a normal distribution it is equal to $1.349\sigma$ (where $\sigma$ is the natural measure of dispersion, called the standard deviation); half the inter-quartile (inter-decile) is called the probable deviation (probable error or semi-inter-quartile distance). If $p=1/6$ or $p=1/10$, the inter-quantile distance is called the inter-sixtile or inter-tentile, respectively.
References
[1] | G.U. Yale, "An introduction to the theory of statistics" , Griffin (1916) |
Inter-quantile width. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Inter-quantile_width&oldid=15850