Graphs versus tables: Effects of data presentation format on judgemental forecasting

https://doi.org/10.1016/0169-2070(95)00634-6Get rights and content

Abstract

We report two experiments designed to study the effect of data presentation format on the accuracy of judgemental forecasts. In the first one, people studied 44 different 20-point time series and forecast the 21st and 22nd points of each one. Half the series were presented graphically and half were in tabular form. Root mean square error (RMSE) in forecasts was decomposed into constant error (to measure bias) and variable error (to measure inconsistency). For untrended data, RMSE was somewhat higher with graphical presentation: inconsistency and an overforecasting bias were both greater with this format. For trended data, RMSE was higher with tabular presentation. This was because underestimation of trends with this format was so much greater than with graphical presentation that it overwhelmed the smaller but opposing effects that were observed with untrended series. In the second experiment, series were more variable but very similar results were obtained.

References (37)

  • N.R. Sanders

    Accuracy of judgmental forecasts: A comparison

    Omega: International Journal of Management Science

    (1992)
  • J.A. Sniezek

    The role of labels in cue probability learning tasks

    Organizational Behavior and Human Decision Processes

    (1986)
  • J.R. Anderson

    The Adaptive Character of Thought

    (1990)
  • P. Angus-Leppan et al.

    The forecasting accuracy of trainee accountants using judgmental and statistical techniques

    Accounting and Business Research

    (1986)
  • F. Bolger et al.

    Context-sensitive heuristics in statistical reasoning

    The Quarterly Journal of Experimental Psychology

    (1993)
  • D. Bunn et al.

    Interaction of judgmental and statistical forecasting methods: Issues and analysis

    Management Science

    (1991)
  • R. Coll et al.

    An experimental study comparing the effectiveness of computer graphics data versus computer tabular data

    IEEE Transactions on Systems, Man and Cybernetics

    (1991)
  • G. DeSanctis

    Computer graphics as decision aids: Directions for research

    Decision Sciences

    (1984)
  • Cited by (68)

    • Forecasting: theory and practice

      2022, International Journal of Forecasting
      Citation Excerpt :

      One of the more straightforward approaches is to change the look and feel of the FSS as well as its presentation style. Harvey and Bolger (1996) found that trends were more easily discernible when the data was displayed in graphical rather than tabular format. Additionally, simple variations in presentation such as line graphs versus point graphs can alter accuracy (Theocharis, Smith, & Harvey, 2018).

    • Using judgment to select and adjust forecasts from statistical models

      2020, European Journal of Operational Research
    • The human factor in supply chain forecasting: A systematic review

      2019, European Journal of Operational Research
    View all citing articles on Scopus
    View full text