An associative and projective diagnosis focused on the analysis of statistical databases characteristic of academic education

The paper presents a distinct manner of statistical analysis, defined by an original associative and projective diagnosis of a set of 10 academic study programmes of the University of Pitesti, generating 244 variables drawn from a larger study that is part of the POSDRU (HRD) contract 156/1.2/G/141632, part of the project known, in its abbreviated form, as NOVA-CURRICULA, a project co-funded by the European Social Fund through the Operational Programme Human Resources Development 2007-2013: “Investing in people”. The associative and projective diagnosis hereby proposed as an innovative method is at the same time regional and county-oriented, referring strictly to the South-Muntenia region and the Argeº county, as the extended pool and the representative pool, in keeping with the statistic 60/60 principle, for the University of Pitesti, and the 10 programmes analysed (in a diverse range, from academic programs in engineering to nursing programmes, etc.). The article tries to find, and – in the author’s opinion – succeeds in identifying, among the multitude of variables aggregated in the database of a multidimensional analysis, associations and correlations that should meet the requirement of specifically modelling the educational supply, in the selection pool, an extensive set of ten academic programmes, using as assumptions and priorities the Europe 2020 strategy, that is an academic education able to link with the labour market, and especially lead to intelligent, sustainable and socially inclusive growth, by means of a software package (EViews); finally, there are a number of remarks and anticipations necessary for a general delimitation of new skills, which are in fact requisite throughout the national academic system, not only in the regional and county real market.