Statistical Noise or Valuable Information

Contemporary marketing research is dominated by empirical studies and quantitative methods for data analysis. In quantitative studies, researchers frequently face the problem of a relatively small number of subjects deviating substantially from the remaining observations. The question arises of how to proceed: Are these deviating observations errors, which need to be corrected, or phenomena worthy of closer investigation? Clemens Pirker's dissertation extensively deals with this question. He documents how published marketing research in leading journals approaches the problem in very pragmatic ways, often simply eliminating substantially deviating cases from the data set or correcting the data by statistical means. Such approaches increase the statistical fit of models and help verify hypotheses. In view of widespread verificationist research, this 'easing' approach is not surprising. But, potentially interesting information contained in deviating data are neglected. An opportunity for scientific progress may be lost. The author presents alternative ways of dealing with outliers, based on a sound discussion from a philosophy of science point of view. He concludes his work with an exhaustive empirical study showing how deviating data may help gaining new insights, not only relevant for scientific progress but also relevant for management decisions. This dissertation offers an interesting repertory of suggestions for all readers interested in scientific progress through empirical studies who are - at the same time - open for sound methodological discussions based on philosophy of science. This work should be obligatory reading in the training of starting academics. Univ. Prof. Dr.