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Another argument against not using interval-based statistical techniques for ordinal data was suggested by Tukey (1986). In Tukey's view, this was a historically unfounded overreaction. In physics before precise measurements were introduced, many physical measurements were only approximately interval scales. For example, temperature measurement was based on liquid-in-glass thermometers. But it is unreasonable not to use a t-test to compare two groups of such temperatures. Tukey argued that researchers painted themselves into a corner on such matters because we were too obsessed with "sanctification" by precision and certainty. If our p-values or confidence intervals are to be sacred, they must be exact. In the practical world, when data values are transformed (. transforming y to sqrt(y), or logy), the p values resulted from different expressions of data would change. Thus, ordinal-scaled data should not be banned from entering the realm of parametric tests. For a review of the debate concerning ordinal- and interval- scaled data, please consult Velleman and Wilkinson (1993).
 

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