Population norms of top sensory magnitudes and S. S. Stevens’ exponents

If S. S. Stevens’ exponents indicate the rates at which sensations grow with increases in sensory intensity, they ought to correlate with the population norms of top sensory magnitudes. Using a comprehensive sample of eight sensory dimensions, the tau coefficient of rank correlation between Stevens’ exponents and the medians of the top sensory magnitudes reported by 305 observers was found to be only +.15 (p>05). With the geometric means tau fell to ?.04. A split-half consistency check on the medians of the population norms suggested that they were not to blame for the low correlation. Direct comparisons of pairs of sensory dimensions on 146 additional observers produced results which confirmed the population norms. Since there is no way of comparing most of the top physical stimuli experienced in everyday life, it is not possible to make a joint prediction from exponents and top stimuli. S. S. Stevens’ exponents thus appear to have little predictive value outside the experimental conditions under which they were measured.     

BRIDGING PHYSIOLOGY AND PHENOMENOLOGY IN DYNAMIC PSYCHOLOGY

R asmussen , E. T ranekjær . Bridging physiology and phenomenology in dynamic psychology. Scand. J. Psychol ., 1961, 2, 161–166.—It is important to distinguish between the immediately experienced (the phenomenological) and the physiological-neurological basis for the phenomenological world, e.g. between beta needs (subjectively experienced states of needing or wanting) and alpha needs (objectively defined, physiological needs). The concept of psychon is introduced and defined as a necessary and sufficient condition in the physiological-neurological system for the existence of a subjective experience; psychon bridges the gap between the physiological and the phenomenological world.     

Orlo Strunk Jr.

Pastoral Psychology -     

Geometrical representation of two methods of linear least squares multiple correlation

Geometrical properties and relationships of the Doolittle and square root methods of multiple correlation, as represented in the variable subspace of an orthogonal person space, are shown. The method of representation is also useful for depicting zero-order and partial correlations, as well as for the more general problem of the combination of variables.