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Speaking Stata: Graphing distributions


  • Nicholas J. Cox

    () (University of Durham, UK)


Graphing univariate distributions is central to both statistical graphics, in general, and StataÕs graphics, in particular. Now that Stata 8 is out, a review of official and user-written commands is timely. The emphasis here is on going beyond what is obviously and readily available, with pointers to minor and major trickery and various user-written commands. For plotting histogram-like displays, kerneldensity estimates and plots based on distribution functions or quantile functions, a large variety of choices is now available to the researcher. Copyright 2004 by StataCorp LP.

Suggested Citation

  • Nicholas J. Cox, 2004. "Speaking Stata: Graphing distributions," Stata Journal, StataCorp LP, vol. 4(1), pages 66-88, March.
  • Handle: RePEc:tsj:stataj:v:4:y:2004:i:1:p:66-88

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    References listed on IDEAS

    1. Philippe Van Kerm, 2003. "Adaptive kernel density estimation," Stata Journal, StataCorp LP, vol. 3(2), pages 148-156, June.
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    Cited by:

    1. Nicholas J. Cox, 2004. "Speaking Stata: Graphing agreement and disagreement," Stata Journal, StataCorp LP, vol. 4(3), pages 329-349, September.
    2. Nicholas J. Cox, 2005. "Speaking Stata: Density probability plots," Stata Journal, StataCorp LP, vol. 5(2), pages 259-273, June.
    3. Stephan Klasen & Simon Lange, 2015. "Accuracy and Poverty Impacts of Proxy Means-Tested Transfers: An Empirical Assessment for Bolivia," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers 164, Courant Research Centre PEG.


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