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An Association Rule General Analytic System (ARGAS) for hypothesis testing and data mining applications

preprint
posted on 19.11.2018 by Rick Parente
The primary purpose of this study was to evaluate the use of an Association Rule General Analytic System (ARGAS) versus the General Linear Model (GLM) for hypothesis testing. Results indicate that the ARGAS provides an better alternative method for testing hypotheses when the assumptions of the GLM are violated. The ARGAS approach can be used with any experimental design to which the GLM can be applied. ARGAS is free of the usual assumptions of the GLM. A second purpose of the study was to illustrate how the ARGAS can be used for hypothesis testing with commonly used experimental designs.

History

Declaration of conflicts of interest

None

Corresponding author email

rparente007@gmail.com

Lead author country

United States

Lead author job role

Higher Education Faculty 4-yr College

Lead author institution

Towson University

Licence

Exports

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