Compstat 1984 pp 341-346 | Cite as

Interpretation of Statistical Software Output: some Behavioral Studies

  • I. W. Molenaar
  • H. Broersma
Conference paper

Summary

Systematic observation of statistical software users is seldom reported in the research literature. This paper describes a pilot study in which 33 subjects scanned graphical or numerical output for deviations from the normal distribution. A task analysis is sketched for stem and leaf display, box plot and numerical characteristics (such as moments and quantiles). The promises and pitfalls of this kind of experiment are briefly evaluated. The companion paper Molenaar (1984) discusses more fully how observation of users may contribute to better human computer interaction.

Keywords

behavioral experiments observation of package users human computer interaction exploratory data analysis. 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Broersma, H.J. (1984), Empirical comparison between presentation forms for data (in Dutch), Heymans Bulletin, 84–701-EX, Vakgroep Statistiek & Meettheorie FSW, University of Groningen.Google Scholar
  2. Cakir, A. et aí. (1983), Visual display terminals, Wiley, New York.Google Scholar
  3. Card, S.K., et al. (1983), The psychology of human-computer interaction, Lawrence Erlbaum Assoc., Hillsdale (N.J.).Google Scholar
  4. Fienberg, S.E. (1979), Graphical methods in statistics, The American Statistician 33, 165–178.Google Scholar
  5. Lourens, P.F. (1984), The formalization of knowledge by specification of subjective probability distributions, an experimental approach, Thesis, University of Groningen.Google Scholar
  6. Matula, R.A. (1981), Effects of visual display units on the eyes: a bibliography (1972–1980), Human Factors 23, 581–586.Google Scholar
  7. McNeil, D.R. (1977), Interactive data analysis, Wiley, New York.Google Scholar
  8. Molenaar, I.W. (1984), Behavioral studies of the software user, Computational Statistics and Data Analysis 2, 1-..Google Scholar
  9. Naveh-Benjamin, M. and Pachella, R.G. (1982), The effect of complexity on interpreting “Chernoff” faces, Human Factors 24, 11–18.Google Scholar
  10. Roberts, T.L. and Moran, T.P. (1983), The evaluation of text editors: methodology and empirical results, Comm. ACM 26, 265–283.CrossRefGoogle Scholar
  11. Scapin, D.L. (1981), Computer commands in restricted language: some aspects of memory and experience, Human Factors 23, 365–375.Google Scholar
  12. Tukey, J.W. (1977), Exploratory data analysis, Addison Wesley, Reading (Mass.) Velleman, P.F. and Hoaglin, D.C. ( 1981 ), Applications, basics and computing of exploratory data analysis, Wadsworth, Belmont.Google Scholar
  13. Wainer, H. (1974), The suspended rootogram and other visual displays, The American Statistician 28, 143–145.Google Scholar
  14. Wainer, H. and Francolini, C.M. (1980), An empirical inquiry concerning human understanding of two-variable color maps, The American Statistician 34, 81–93.CrossRefGoogle Scholar
  15. Wainer, H. and Thissen, D. (1981), Graphical data analysis, Annual Review of Psychology 32, 191–241.CrossRefGoogle Scholar
  16. Wesselink, G. (1983), Exploring in the packages CADA, SPSS and TTWESP: the box plot and the stem and leaf display (in Dutch), Heymans Bulletin 83–679-RP, Vakgroep Statistiek en Meettheorie FSW, University of Groningen.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1984

Authors and Affiliations

  • I. W. Molenaar
    • 1
  • H. Broersma
    • 1
  1. 1.GroningenThe Netherlands

Personalised recommendations