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Tri–Squared Mean Cross Comparative Analysis: An Advanced Post Hoc Qualitative and Quantitative Metric for a More In–Depth Examination of the Initial Research Outcomes of the Tri–Square Test

James Edward Osler II*

North Carolina Central University.

Periodicity:October - December'2013
DOI : https://doi.org/10.26634/jet.10.3.2504

Abstract

This monograph provides an epistemological rational for the design of an advanced novel analysis metric. The metric is designed to analyze the outcomes of the Tri–Squared Test. This methodology is referred to as: “Tri–Squared Mean Cross Comparative Analysis” (given the acronym TSMCCA). Tri–Squared Mean Cross Comparative Analysis involves the computation and in–depth study of means extracted from an initial Tri–Squared Test. The Tri–Squared Testhad an established level of statistical significance that provided the grounds for further Post Hoc investigation. The TSMCCA statistic is an Advanced Post Hoc test of the transformative process of qualitative data into quantitative outcomes through the Tri–Squared Test first introduced in the Journal on Mathematics. Advanced statistical analytics are involved in the TSMCCA mathematical model that allows for critical analysis of mean scores on item results.This type of in–depth post hoc statistical analysis permits a higher level of Tri–Squared meta–analytical investigative inquiry.

Keywords

Array, Categorical, Comparative, Investigation, Mathematical Model, Mean, Outcomes, Post Hoc, Research, Triangulation, Trichotomy, Tri–Associative Analytics, Tri–Squared, Tri–Squared Mean Cross Comparative Analysis(TSMCCA), Statistics, And Variables.

How to Cite this Article?

Osler, J. E. (2013). Tri–Squared Mean Cross Comparative Analysis: An Advanced Post Hoc Qualitative And Quantitative Metric For A More In–Depth Examination Of The Initial Research Outcomes Of The Tri–Square Test. i-manager’s Journal of Educational Technology, 10(3), 35-41. https://doi.org/10.26634/jet.10.3.2504

References

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[7]. Osler, J. E. (2013c). Algorithmic Triangulation Metrics for Innovative Data Transformation: Defining the Application Process of the Tri–Squared Test. April–June, Journal on Mathematics,2 (2), pp. 10–16.

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