Exploratory data analysis

Last updated on Feb 26, 2026
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Definition: Exploratory Data Analysis (EDA) is a well-established statistical tradition that provides conceptual and computational tools for discovering patterns in data to foster hypothesis development and refinement. These tools and attitudes complement the use of hypothesis tests used in confirmatory data analysis (CDA). Even when well-specified theories are held, EDA helps one interpret the results of CDA and may reveal unexpected or misleading patterns in the data.

Related terms: Confirmatory analyses, Data-driven research, Exploratory research

References:

  • Behrens, J. T. (1997). Principles and procedures of exploratory data analysis. Psychological Methods, 2(2), 131–160. https://doi.org/10.1037/1082-989X.2.2.131
  • Box, G. E. P. (1976). Science and statistics. Journal of the American Statistical Association, 71(356), 791–799.
  • Tukey, J. W. (1977). Exploratory data analysis. Addison-Wesley.
  • Wagenmakers, E. J., Wetzels, R., Borsboom, D., van der Maas, H. L., & Kievit, R. A. (2012). An agenda for purely confirmatory research. Perspectives on Psychological Science, 7(6), 632–638. https://doi.org/10.1177/1745691612463078

Originally drafted by: Jenny Terry

Reviewed by: Helena Hartmann, Timo Roettger, Charlotte R. Pennington, FlĂĄvio Azevedo