A graphical procedure for distinguishing between two data analysis pitfalls |
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| Authors: | Michael E Tarter William R Freeman |
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| Institution: | 1. Department of Biomedical and Environmental Health Sciences , University of California , Berkeley;2. West Coast Cancer Foundation , San Francisco, California |
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| Abstract: | This paper presents a graphical procedure for simultaneously distinguishing between two commonly encountered data anomaliesWhen applied in the context of one anomaly, a family of parallel lines will be estimated, and when applied in the contextofthe second anomaly, a family of lines, whose members all pass through the same point, will be estimated. It is shown that the procedure can be applied effectively using samples containing as few as two hundred bivariate observations. |
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| Keywords: | Lognormal heteroscedasticity linear regression bivariate density estimation nonparametric estimation |
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