Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts.
When information is derived from instrument readings 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. When the observations are discrete but the underlying phenomenon is continuous then smoothing and interpolation are often 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.
These are common techniques used in data reduction.
- Order by some aspect of size.
- Table diagonalization, whereby rows and columns of tables are re-arranged to make patterns easier to see (refer to the diagram).
- Round drastically to one, or at most two, effective digits (effective digits are ones that vary in that part of the data).
- Use averages to provide a visual focus as well as a summary.
- Use layout and labeling to guide the eye.
- Remove Chartjunk, such as pictures and lines.
- Give a brief verbal summary.
- http://business.nmsu.edu/~mhyman/M610_Articles/Ehrenberg_Marketing_Research_2001.pdf Data, but No Information: Presentation really is everything — or close to it. By Andrew Ehrenberg