ABSTRACT
Why identification is relevant for model construction? In 1922, R. A. Fisher pointed out that, in spite of the large amount of fruitful applications of statistics, its basic principles were still in a “state of obscurity” and that “during the recent rapid development of practical methods, fundamental problems have been ignored” (Fisher, 1922, p. 310). This evaluation led Fisher to define the scope of statistical methods as the reduction of data. “No human mind is capable of grasping in its entirety the meaning of any considerable quantity of numerical data” (Fisher, 1973, p. 6). Consequently, data should be replaced by a relatively few quantity of values that should contain the relevant information provided by the original data.
