Music and Science: A Guide to Empirical Research

This repository contains the electronic materials for Routledge book titled Music and Science: Guide to Empirical Research by Tuomas Eerola, at Durham University and Music and Science Lab. The book is scheduled to be published in 2024.

The materials are Jupyter notebooks with code examples in R or Python). The notebooks are designed to be run in Google Colab within a browser. Colab service is free and does not require any installations or software. It is also possible to run the notebooks within a Jupyter server in your own computer or to use the code directly in R or in Python. See technical notes about the notebooks and package versions in Colab.

The public-facing version of this repository is at https://tuomaseerola.github.io/emr/. See citation for bibliographic details of the book.

ver 25/4/2024

Contents

Website (preferred link)	Jupyter	Colab	Language
Chapter 1: Introduction
Ch. 1 - Notebook basics	Chapter1.ipynb		R
Chapter 2: History
Ch. 2 Examples
Chapter 3: Contemporary Empirical Music Research
Ch. 3 - Historic profiles	Chapter3.ipynb		R
Chapter 4: Methods and Research Designs
Ch. 4 - Correlations	Chapter4.ipynb		R
Chapter 5: Sources of Information
Chapter 6: Data Organisation and Summaries
Ch. 6 - Using R	Chapter6.1.ipynb		R
Ch. 6 - Data organisation	Chapter6.2.ipynb		R
Ch. 6 - Diagnostics	Chapter6.3.ipynb		R
Ch. 6 - Outliers	Chapter6.4.ipynb		R
Chapter 7: Statistical Analysis
Ch. 7 - Inferential statistics	Chapter7.ipynb		R
Chapter 8: Reporting
Chapter 9: Analysis of Scores and Performances
Ch. 9 - Music analysis	Chapter9.1.ipynb		Python
Ch. 9 - Event counts	Chapter9.2.ipynb		Python
Ch. 9 - Key-Finding	Chapter9.3.ipynb		Python
Ch. 9 - Expressive timing	Chapter9.4.ipynb		R
Ch. 9 - Synchronisation	Chapter9.5.ipynb		R
Chapter 10: Analysis of Audio
Ch. 10 - Basics (sines)	Chapter10.1.ipynb		Python
Ch. 10 - Spectrum and envelope	Chapter10.2.ipynb		Python
Ch. 10 - Physical	Chapter10.3.ipynb		Python
Ch. 10 - Perceptual	Chapter10.4.ipynb		Python
Ch. 10 - Semantic	Chapter10.5.ipynb		Python
Chapter 11: Corpus Studies
Ch. 11 - Genre Classification	Chapter11.2.ipynb		Python
Ch. 11 - Synchrony	Chapter11.3.qmd		R
Chapter 12: Summary and Future Directions
Appendix
Citation			Markdown
Technical			Markdown
Links			Markdown
Version (R)	Version_R.ipynb		R
Version (Python)	Version_Python.ipynb		Python