For two independently drawn samples of data, a novel statistical test is proposed for the null hypothesis that both samples originate from the same population. The underlying distribution function does not need to be known but must be continuous, i.e., it is a nonparametric test. It is demonstrated for suitable examples that the test is easy to apply and is at least as powerful as the commonly used nonparametric tests, i.e., the Kolmogorov-Smirnov, the Cramer-von Mises, and the Wilcoxon tests.
Biometrics is a scientific journal emphasizing the role of statistics and mathematics in the biological sciences. Its object is to promote and extend the use of mathematical and statistical methods in pure and applied biological sciences by describing developments in these methods and their applications in a form readily assimilable by experimental scientists. JSTOR provides a digital archive of the print version of Biometrics. The electronic version of Biometrics is available at http://www.blackwell-synergy.com/servlet/useragent?func=showIssues&code;=biom. Authorized users may be able to access the full text articles at this site.
The International Biometric Society is an international society for the advancement of biological science through the development of quantitative theories and the application, development and dissemination of effective mathematical and statistical techniques. The Society welcomes as members biologists, mathematicians, statisticians, and others interested in applying similar techniques.
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Biometrics
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