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Explore advanced corpus studies and statistical analysis techniques in computational music theory through this 48-minute lecture from MIT's Computational Music Theory and Analysis course. Examine Problem Set 4 solutions and engage in detailed analysis of works by Bach and Haydn, comparing close versus distant listening methodologies. Learn about upcoming Problem Set 5 requirements and discover additional tools available in the music21 Python library for computational music analysis. Gain practical insights into applying statistical methods to large musical datasets and understand how computational approaches can reveal patterns and structures in classical compositions that may not be apparent through traditional analytical methods.
