<article_id>JMAT_V3_N4_RP1</article_id>
<title>Introducing Trinova: “Trichotomous Nomographical Variance” a Post Hoc Advanced Statistical Test of Between and Within Group Variances of Trichotomous Categorical and Outcome Variables of a Significant Tri–Squared Test</title>
<author>James Edward Osler II</author>
<journal>Journal on Mathematics</journal>
<issn>2277-5137</issn>
<volume>3</volume>
<issue>4</issue>
<first_page>1</first_page>
<last_page>14</last_page>
<keywords>Analytics, Instrument, Investigation, Mathematical Model, Outcomes, Post Hoc, Research, Static Test, Statistics, Trichotomy, Tri–Squared, Tri–Squared Tests, Trinova, Trivariant, Variables, Variance</keywords>
<abstract>This monograph provides an epistemological rational for the Trinova Post Hoc test methodology. Trinova is an in–depth [Trichotomous Nomographical Variance] statistical procedure for the internal testing of the transformative process of qualitative data, into quantitative outcomes through the Tri–Squared Test first introduced in i-manager’s Journal on Mathematics, and further detailed in the Journal on Educational Technology, Journal on School Educational Technology, and in Journal on Educational Psychology. Trinova is an advanced statistical measure that is designed to check the validity and reliability of a Tri–Squared Test. This is a novel approach to advanced statistical post hoc Tri–Squared data analysis. It adds considerable value to the mixed methods approach of research design that involves the holistic combination and comparison of qualitative and quantitative data outcomes. A sequential Trinova mathematical model is provided, that illustrates the entire process of advanced statistical Trichotomous inquiry.</abstract>
<date>October - December 2014</date>
<copyright>Copyright &copy; 2014 i-manager publications. All rights reserved.</copyright>
<publisher>i-manager Publications</publisher>
<article_url>http://www.imanagerpublications.com/Article.aspx?ArticleId=3184</article_url>