Gathered data is frequently not in a numerical form allowing immediate appliance of the quantitative mathematical-statistical methods. In this paper are some basic aspects examining how quantitative-based statistical methodology can be utilized in the analysis of qualitative data sets. The transformation of qualitative data into numeric values is considered as the entrance point to quantitative analysis. Concurrently related publications and impacts of scale transformations are discussed. Subsequently, it is shown how correlation coefficients are usable in conjunction with data aggregation constrains to construct relationship modelling matrices. For illustration, a case study is referenced at which ordinal type ordered qualitative survey answers are allocated to process defining procedures as aggregation levels. Finally options about measuring the adherence of the gathered empirical data to such kind of derived aggregation models are introduced and a statistically based reliability check approach to evaluate the reliability of the chosen model specification is outlined. 1. Introduction In this paper some aspects are discussed how data of qualitative category type, often gathered via questionnaires and surveys, can be transformed into appropriate numerical values to enable the full spectrum of quantitative mathematical-statistical analysis methodology. Therefore the impacts of the chosen valuation-transformation from ordinal scales to interval scales and their relations to statistical and measurement modelling are studied. This is applied to demonstrate ways to measure adherence of quantitative data representation to qualitative aggregation assessments-based on statistical modelling. Finally an approach to evaluate such adherence models is introduced. Concurrent a brief epitome of related publications is given and examples from a case study are referenced. Gathering data is referencing a data typology of two basic modes of inquiry consequently associated with “qualitative” and “quantitative” survey results. Thereby “quantitative” is looked at to be a response given directly as a numeric value and “qualitative” is a nonnumeric answer. This differentiation has its roots within the social sciences and research. A brief comparison of this typology is given in [1, 2]. A refinement by adding the predicates “objective” and “subjective” is introduced in [3]. An elaboration of the method usage in social science and psychology is presented in [4]. A precis on the qualitative type can be found in [5] and for the quantitative type in [6]. A comprehensive book about
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