A bibliography of statistical applications in musicology

Abstract

Statistical applications in musicology appear in widely scattered publications. The present bibliography, mainly of English language publications, extends back to the beginning of the present century. The analysis of musical scores is emphasized, but applications in the social sciences arc also touched upon, as well as those to performance studies and algorithmic composition. Statistical techniques include simple summarization, graphical methods, time series analysis, information theory, Zipf's law, Markov chains, fractals, and neural networks. Several cases of misapplication of statistics are noted. Commentary is provided on the field and its sub-fields.

Evolutionary Music and the Zipf-Mandelbrot Law: Developing Fitness Functions for Pleasant Music

“…Some attempt to understand this meaning and its effect on the listener by dissecting the aesthetic experience in terms of separable, discrete sounds. Others attempt to find it in terms of grouping stimuli into patterns and studying their hierarchical organization [4], [10], [11], [15], [16]. Meyer [13, p. 342] suggests that emotional states in music (sad, angry, happy, etc.)…”