Abstract

The analysis of variance is a statistical technique widely used in the design of experiments and different research areas. It has been modeled using a classical or frequentist approach. With the computational power that is currently available, the Bayesian approach is an essential statistical tool related to hypothesis testing. However, conformity with classical techniques, ignorance of Bayesian statistics, and lack of easy-to-use software are obstacles to its frequent application. In this work, the use of a reproducible statistical package in R is proposed. It presents options to perform an analysis of variance in a classical (frequentist) and Bayesian way when the assumptions of the frequentist approach are not met or when a level of more specific inference such as quantifying the evidence provided by a data set for a given hypothesis, with the possibility of contributing to the understanding of the rejection or not of the statistical hypotheses raised, through interactive graphics presented in an emerging Shiny panel.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.