caa a22 4500 386326401 CHVBK 20180307111654.0 cr unu---uuuuu 161130e198904 xx s 000 0 eng 10.1017/S0014479700016665 doi S0014479700016665 pii (NATIONALLICENCE)cambridge-10.1017/S0014479700016665 Finney D. J. International Statistical Institute Research Centre, 428, Prinses Beatrixlaan, 2270 AZ Voorburg, Netherlands Was This in Your Statistics Textbook? V. Transformation of Data [Elektronische Daten] [D. J. Finney] Additivity, variance homogeneity, and normality are often regarded as prerequisites for analysis of variance. Although they are desirable, their truth is never certain; they are important to probability levels in significance tests, but not to the general informativeness of the analysis. Transformation of data may improve conformity to these desiderata at the cost of producing results on a scale ill-suited to the objectives of the experiment. In this paper the generalized power transformation and the inverse sine transformation are described, and the practical problems of choosing an optimal transformation discussed. An ideal choice can seldom be based on the evidence of one experiment, and adopting the same transformation for a series of similar experiments is usually more helpful than a search for the ‘best'. Warnings are given about inappropriate guides to the choice of transformation. In some experiments, separate analyses for two or more obviously distinct sets of treatments may be more rewarding than any attempt to find a transformation that will enable all to be handled at once. When one or two treatments (or treatment combinations in a factorial experiment) show data wildly out of line with all others, consideration of reasons should precede and possibly replace any approach through transformation. A sound general principle is that data are usually most clearly interpreted on the original scale of measurement. Therefore, transformations should be avoided unless clearly necessary; by this advice, I do not imply prohibition. Finally, attention must be given to the presentation of results; the most effective presentation does not necessarily employ a transformation or other special device adopted earlier in a statistical analysis. Copyright © Cambridge University Press 1989 Experimental Agriculture Cambridge University Press 25/2(1989-04), 165-175 0014-4797 25:2<165 1989 25 EAG https://doi.org/10.1017/S0014479700016665 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1017/S0014479700016665 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Finney D. J. International Statistical Institute Research Centre, 428, Prinses Beatrixlaan, 2270 AZ Voorburg, Netherlands NATIONALLICENCE 773 0- Experimental Agriculture Cambridge University Press 25/2(1989-04), 165-175 0014-4797 25:2<165 1989 25 EAG CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence SWISSBIB 386163332 BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-cambridge