Quantile plots: New planks in an old campaign
Nicholas Cox
United Kingdom Stata Users' Group Meetings 2016 from Stata Users Group
Abstract:
Quantile plots show ordered values (raw data, estimates, residuals, whatever) against rank or cumulative probability or a one-to-one function of the same. Even in a strict sense, they are almost 200 years old. In Stata, quantile, qqplot, and qnorm go back to 1985 and 1986. So why any fuss? The presentation is built on a long-considered view that quantile plots are the best single plot for univariate distributions. No other kind of plot shows so many features so well across a range of sample sizes with so few arbitrary decisions. Both official and user-written programs appear in a review that includes side-by-side and superimposed comparisons of quantiles for different groups and comparable variables. Emphasis is on newer, previously unpublished work, with focus on the compatibility of quantiles with transformations; fitting and testing of brand-name distributions; quantile-box plots as proposed by Emanuel Parzen (1929–2016); equivalents for ordinal categorical data; and the question of which graphics best support paired and two-sample t and other tests. Commands mentioned include distplot, multqplot, and qplot (Stata Journal) and mylabels, stripplot, and hdquantile (SSC).
Date: 2016-09-16
References: Add references at CitEc
Citations:
Downloads: (external link)
http://repec.org/usug2016/cox_uksug16.pptx (application/x-ms-powerpoint)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:boc:usug16:03
Access Statistics for this paper
More papers in United Kingdom Stata Users' Group Meetings 2016 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().