EXPLANATORY METHODS OF MARKETING DATA ANALYSIS – THEORETICAL AND METHODOLOGICAL CONSIDERATIONS Lecturer Manuela Rozalia GABOR „Petru Maior” University,Tg. Mureş Abstract: Explanatory methods of data analysis – also named by some authors supervised learning methods - enable researchers to identify and analyse configurations of relations between two or several variables, most of them with a high accuracy, as there is possibility of testing statistic significance by calculating the confidence level associated with validation of relation concerned across the entire population and not only the surveyed sample. The paper shows some of these methods, respectively: variance analysis, covariance analysis, segmentation and discriminant analysis with the mention - for every method – of applicability area for marketing research. Key words: explanatory methods, ANOVA, ANCOVA, segmentation and discriminant analysis Introduction The data analysis methods are unlike the descriptive ones, in that, they divide variables in dependent and independent and study the independence relations and not the interdependence relations as the descriptive methods. Most times, they are also preceded by the descriptive analysis methods and as a result, both explained variable and the explanatory ones are defined in relation to the problem context. Relations between economic phenomena and processes occur as statistic relations (stochastic) and they can be classified according to several criteria, as follows (table no. 1): Table 1 Classification of statistic relations between economic phenomena and processes Classification criterion Types of relations Number of characteristics that are surveyed Simple relations – a single factor characteristic with basic nature; Multiple relations – more than two factor characteristics. How characteristics are expressed: Relations between statistics variables measured on metric scales; Relations between statistic variables expressed non- metric. Direction of relations: Direct relations; Inverse relations Analytical expression Linear relations; Non-linear relations. Time when relation is accomplished: Concurrent or synchronous relations Asynchronous or gap relations. Relation nature: Causal ; Reciprocal No relation, both phenomena being determined by a third factor.