Association rules are a fundamental class of patterns that exist in data. The key strength of association rule mining is its completeness. It finds all associations in the data that satisfy the user specified minimum support and minimum confidence constraints. This strength, however, comes with a major drawback. It often produces a huge number of associations. This is particularly true for data sets whose attributes are highly correlated. The huge number of associations makes it very difficult, if not impossible, for a human user to analyze in order to identify those interesting/useful ones. In this paper, we propose a novel technique to overcome this problem. The technique first prunes the discovered associations to remove those insignificant associations, and then finds a special subset of the unpruned associations to form a summary of the discovered associations. We call this subset of associations the direction setting (DS) rules as they set the directions that are followed by the...

The consequences of prejudice against accepting the null hypothesis were examined through (a) a mathematical model intended to stimulate the research-publication process and (b) case studies of apparent erroneous rejec-tions of the null hypothesis in published psychological research. The input parameters for the model characterize investigators ' probabilities of selecting a problem for which the null hypothesis is true, of reporting, following up on, or abandoning research when data do or do not reject the null hypothesis, and they characterize editors ' probabilities of publishing manuscripts concluding in favor of or against the null hypothesis. With estimates of the input parameters based on a questionnaire survey of a sample of social psychologists, the model output indicates a dysfunctional research-publication system. Particularly, the model indicates that there may be relatively few publications on problems for which the null hypothesis is (at least to a reasonable approximation) true, and of these, a high proportion will erroneously reject the null hypothesis. The case studies provide additional support for this conclusion. Accordingly, it is

this report was facilitated by grants from National Science Foundation (GS-3050) and U.'S. Public Health Service (MH-20527-02). Although they should not be held responsible for positions espoused herein, I am very grateful to the following for providing comments on earlier drafts: Marl R. Jones, Paul Isaac, David Bakan, Timothy C. Brock, Bibb Latan6, Thomas M. Ostrom, Hanan C. Selvin, Martin Fishbein, Zick Rubin, and Richard A. Zeller