On visualisation of statistical data

In many applications a need often arises to represent numerical data to give greater visual impact. Whether the data consists of demographic information or forms a listing of financial business trends, their interpretation and meaning is simpler to comprehend through a pictorial representation. The requirement in practice is such that visualisation needs to take place on-the-fly. This implies that the process of transforming static data into a diagrammatic form needs to be dynamic. Whereas most authors have addressed the scenario by employing cubic interpolation to the given set of data points, we discuss the suitability of using a quadratic approach. We introduce the general quadrature spline, its attractions, and its limitations, together with some thoughts as to how the conic (quadratic) spline could be adapted to meet most needs.