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Speaking Stata: Density probability plots

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  • Nicholas J. Cox

    (University of Durham, UK)

Abstract

Density probability plots show two guesses at the density function of a continuous variable, given a data sample. The first guess is the density function of a specified distribution (e.g., normal, exponential, gamma, etc.) with appropriate parameter values plugged in. The second guess is the same density function evaluated at quantiles corresponding to plotting positions associated with the sample’s order statistics. If the specified distribution fits well, the two guesses will be close. Such plots, suggested by Jones and Daly in 1995, are explained and discussed with examples from simulated and real data. Comparisons are made with histograms, kernel density estimation, and quantile–quantile plots. Copyright 2005 by StataCorp LP.

Suggested Citation

  • Nicholas J. Cox, 2005. "Speaking Stata: Density probability plots," Stata Journal, StataCorp LP, vol. 5(2), pages 259-273, June.
    • Handle: RePEc:tsj:stataj:v:5:y:2005:i:2:p:259-273
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    References listed on IDEAS

    as
    1. Nicholas J. Cox, 2004. "Speaking Stata: Graphing distributions," Stata Journal, StataCorp LP, vol. 4(1), pages 66-88, March.
    2. Hazelton M.L., 2003. "A Graphical Tool for Assessing Normality," The American Statistician, American Statistical Association, vol. 57, pages 285-288, November.
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    Cited by:

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    2. Tindara Abbate & Fabrizio Cesaroni & Angelo Presenza, 2021. "Knowledge transfer from universities to low- and medium-technology industries: evidence from Italian winemakers," The Journal of Technology Transfer, Springer, vol. 46(4), pages 989-1016, August.
    3. Chandan Sharma, 2018. "Productivity and Size of Firms: Evidence from Indian Manufacturing," Economics Bulletin, AccessEcon, vol. 38(2), pages 791-798.

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