Data reduction

Data reduction

Data Reduction is the transformation of numerical or alphabetical digital information derived empirical or experimentally into a corrected, ordered, and simplified form.

Columns and rows are moved around until a diagonal pattern appears, thereby making it easy to see patterns in the data.

When the information is derived from instrument readings then there may also be a transformation from analog to digital form. When the data are already in digital form the 'reduction' of the data typically involves some editing, scaling, coding, sorting, collating, and producing tabular summaries, and when the observations are discrete but the underlying phenomenon is continuous then smoothing and interpolation are likely to be needed. Often the data reduction is undertaken in the presence of reading or measurement errors. Some idea of the nature of these errors is needed before the most likely value may be determined.

“Data Reduction” rules which have been suggested include:

  1. Order by some aspect of size.
  2. 'Diagonalize' tables, so that unordered categories are re-arranged to make patterns easier to see. [1]
  3. Use averages to provide a visual focus as well as a summary.
  4. Use layout and labeling to guide the eye.
  5. Remove Chartjunk, such as pictures and lines.
  6. Give a brief verbal summary.[2]


  1. ^ Jacques Bertin, Semiology of Graphics: Diagrams, Networks, Maps. ESRI Press, 2010, 168-169.</ref# Round drastically to one, or at most two, effective digits (effective digits are ones that vary in that part of the data).
  2. ^ Data, but No Information: Presentation really is everything — or close to it. By Andrew Ehrenberg


  • Ehrenberg, Andrew S. C. (1975,1981), Data Reduction, John Wiley, Chichester. Reprinted in the Journal of Empirical Generalisations in Marketing Science, 2000, 5, 1-391
  • Ehrenberg, Andrew S. C. (1982) A Primer in Data Reduction: An Introductory Statistics Ehrenberg

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