updates

Author: tuomaseerola

docs/index.html

@@ -352,10 +352,16 @@ <h1 class="title">Music and Science – Guide to Empirical Music Research (Book)
 I am currently working towards finishing this file.
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 <p>This repository contains the electronic materials for <em>Routledge</em> book titled <strong><a href="https://tuomaseerola.github.io/emr/">Music and Science – Guide to Empirical Music Research</a></strong> by <a href="https://tuomaseerola.github.io/about/">Tuomas Eerola</a>, at <a href="https://www.durham.ac.uk">Durham University</a> and <a href="https://musicscience.net">Music and Science Lab</a>. The book is scheduled to be published in 2024.</p>
-<p>The materials are <a href="https://quarto.org">Quarto</a> notebooks with code examples in <a href="https://www.r-project.org/">R</a> or <a href="https://www.python.org/">Python</a>. The notebooks can be run in three ways: 1. Using <a href="https://colab.research.google.com/">Google Colab</a> using a browser. Colab service is free and does not require any installations or software. 2. Using a local <a href="https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/index.html">Jupyter server in your own computer</a> 3. Using the code directly in R or in Python in local machine.</p>
-<p>The repository also works as a guide and replicates all computational and statistical aspects mentioned in the book. See <a href="./Technical.html">technical notes</a> about the notebooks and package versions.</p>
-<p>The public-facing version of this repository is at <a href="https://tuomaseerola.github.io/emr/">https://tuomaseerola.github.io/emr/</a>. See <a href="./Citation.html">citation</a> for bibliographic details of the book.</p>
-<p><code>ver 5/4/2024 15:24</code></p>
+<p>The materials are <a href="https://quarto.org">Quarto</a> notebooks with code examples in <a href="https://www.r-project.org/">R</a> or <a href="https://www.python.org/">Python</a>. The notebooks can be used in four ways:</p>
+<ol type="1">
+<li>Explore the code and data directly in R or in Python in your local machine.</li>
+<li>Use the <strong>Jupyter</strong> notebooks locally in a <a href="https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/index.html">server</a>.</li>
+<li>Run the notebooks through <a href="https://colab.research.google.com/"><strong>Google Colab</strong></a> in a browser (it is free and does not require any additional software).</li>
+<li>Study this <strong>website</strong> to learn how to replicate the computational and statistical aspects mentioned in the book.</li>
+</ol>
+<p>See <a href="./Technical.html">technical notes</a> about the notebooks and <a href="./Version_R.html">package versions</a>.</p>
+<p>The public-facing version of this repository is at <a href="https://tuomaseerola.github.io/emr/">https://tuomaseerola.github.io/emr/</a>. See <a href="./Citation.html">citation</a> for the bibliographic details of the book.</p>
+<p><code>Ver: 5/4/2024 16:18</code></p>
 <section id="contents" class="level1">
 <h1>Contents</h1>
 <table class="table">

docs/search.json

@@ -504,7 +504,7 @@
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     "title": "Music and Science – Guide to Empirical Music Research (Book)",
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-    "text": "This repository contains the electronic materials for Routledge book titled Music and Science – Guide to Empirical Music Research by Tuomas Eerola, at Durham University and Music and Science Lab. The book is scheduled to be published in 2024.\nThe materials are Quarto notebooks with code examples in R or Python. The notebooks can be run in three ways: 1. Using Google Colab using a browser. Colab service is free and does not require any installations or software. 2. Using a local Jupyter server in your own computer 3. Using the code directly in R or in Python in local machine.\nThe repository also works as a guide and replicates all computational and statistical aspects mentioned in the book. See technical notes about the notebooks and package versions.\nThe public-facing version of this repository is at https://tuomaseerola.github.io/emr/. See citation for bibliographic details of the book.\nver 5/4/2024 15:24\n\nContents\n\n\n\nWebsite (preferred link)\nJupyter\nColab\nLanguage\n\n\n\n\nChapter 1: Introduction\n\n\n\n\n\n  Ch. 1 - Notebook basics\nChapter1.ipynb\n\nR\n\n\nChapter 2: History\n\n\n\n\n\n  Ch. 2 Examples\n\n\n\n\n\nChapter 3: Contemporary Empirical Music Research\n\n\n\n\n\n  Ch. 3 - Historic profiles\nChapter3.ipynb\n\nR\n\n\nChapter 4: Methods and Research Designs\n\n\n\n\n\n  Ch. 4 - Correlations\nChapter4.ipynb\n\nR\n\n\nChapter 5: Sources of Information\n\n\n\n\n\nChapter 6: Data Organisation and Summaries\n\n\n\n\n\n  Ch. 6 - Using R\nChapter6.1.ipynb\n\nR\n\n\n  Ch. 6 - Data organisation\nChapter6.2.ipynb\n\nR\n\n\n  Ch. 6 - Diagnostics\nChapter6.3.ipynb\n\nR\n\n\n  Ch. 6 - Outliers\nChapter6.4.ipynb\n\nR\n\n\nChapter 7: Statistical Analysis\n\n\n\n\n\n  Ch. 7 - Inferential statistics\nChapter7.ipynb\n\nR\n\n\nChapter 8: Reporting\n\n\n\n\n\nChapter 9: Analysis of Scores and Performances\n\n\n\n\n\n  Ch. 9 - Music analysis\nChapter9.1.ipynb\n\nPython\n\n\n  Ch. 9 - Event counts\nChapter9.2.ipynb\n\nPython\n\n\n  Ch. 9 - Key-Finding\nChapter9.3.ipynb\n\nPython\n\n\n  Ch. 9 - Expressive timing\nChapter9.4.ipynb\n\nR\n\n\n  Ch. 9 - Synchronisation\nChapter9.5.ipynb\n\nR\n\n\nChapter 10: Analysis of Audio\n\n\n\n\n\n  Ch. 10 - Basics (sines)\nChapter10.1.ipynb\n\nPython\n\n\n  Ch. 10 - Spectrum and envelope\nChapter10.2.ipynb\n\nPython\n\n\n  Ch. 10 - Physical\nChapter10.3.ipynb\n\nPython\n\n\n  Ch. 10 - Perceptual\nChapter10.4.ipynb\n\nPython\n\n\n  Ch. 10 - Semantic\nChapter10.5.ipynb\n\nPython\n\n\nChapter 11: Corpus Studies\n\n\n\n\n\n  Ch. 11 - Genre Classification\nChapter11.2.ipynb\n\nPython\n\n\n  Ch. 11 - Synchrony\nChapter11.3.qmd\n\nR\n\n\nChapter 12: Summary and Future Directions\n\n\n\n\n\nAppendix\n\n\n\n\n\n  Citation\n\n\nMarkdown\n\n\n  Technical\n\n\nMarkdown\n\n\n  Links\n\n\nMarkdown\n\n\n  Version (R)\nVersion_R.ipynb\n\nR\n\n\n  Version (Python)\nVersion_Python.ipynb\n\nPython\n\n\n\n\n\n\n\n Back to top"
+    "text": "This repository contains the electronic materials for Routledge book titled Music and Science – Guide to Empirical Music Research by Tuomas Eerola, at Durham University and Music and Science Lab. The book is scheduled to be published in 2024.\nThe materials are Quarto notebooks with code examples in R or Python. The notebooks can be used in four ways:\n\nExplore the code and data directly in R or in Python in your local machine.\nUse the Jupyter notebooks locally in a server.\nRun the notebooks through Google Colab in a browser (it is free and does not require any additional software).\nStudy this website to learn how to replicate the computational and statistical aspects mentioned in the book.\n\nSee technical notes about the notebooks and package versions.\nThe public-facing version of this repository is at https://tuomaseerola.github.io/emr/. See citation for the bibliographic details of the book.\nVer: 5/4/2024 16:18\n\nContents\n\n\n\nWebsite (preferred link)\nJupyter\nColab\nLanguage\n\n\n\n\nChapter 1: Introduction\n\n\n\n\n\n  Ch. 1 - Notebook basics\nChapter1.ipynb\n\nR\n\n\nChapter 2: History\n\n\n\n\n\n  Ch. 2 Examples\n\n\n\n\n\nChapter 3: Contemporary Empirical Music Research\n\n\n\n\n\n  Ch. 3 - Historic profiles\nChapter3.ipynb\n\nR\n\n\nChapter 4: Methods and Research Designs\n\n\n\n\n\n  Ch. 4 - Correlations\nChapter4.ipynb\n\nR\n\n\nChapter 5: Sources of Information\n\n\n\n\n\nChapter 6: Data Organisation and Summaries\n\n\n\n\n\n  Ch. 6 - Using R\nChapter6.1.ipynb\n\nR\n\n\n  Ch. 6 - Data organisation\nChapter6.2.ipynb\n\nR\n\n\n  Ch. 6 - Diagnostics\nChapter6.3.ipynb\n\nR\n\n\n  Ch. 6 - Outliers\nChapter6.4.ipynb\n\nR\n\n\nChapter 7: Statistical Analysis\n\n\n\n\n\n  Ch. 7 - Inferential statistics\nChapter7.ipynb\n\nR\n\n\nChapter 8: Reporting\n\n\n\n\n\nChapter 9: Analysis of Scores and Performances\n\n\n\n\n\n  Ch. 9 - Music analysis\nChapter9.1.ipynb\n\nPython\n\n\n  Ch. 9 - Event counts\nChapter9.2.ipynb\n\nPython\n\n\n  Ch. 9 - Key-Finding\nChapter9.3.ipynb\n\nPython\n\n\n  Ch. 9 - Expressive timing\nChapter9.4.ipynb\n\nR\n\n\n  Ch. 9 - Synchronisation\nChapter9.5.ipynb\n\nR\n\n\nChapter 10: Analysis of Audio\n\n\n\n\n\n  Ch. 10 - Basics (sines)\nChapter10.1.ipynb\n\nPython\n\n\n  Ch. 10 - Spectrum and envelope\nChapter10.2.ipynb\n\nPython\n\n\n  Ch. 10 - Physical\nChapter10.3.ipynb\n\nPython\n\n\n  Ch. 10 - Perceptual\nChapter10.4.ipynb\n\nPython\n\n\n  Ch. 10 - Semantic\nChapter10.5.ipynb\n\nPython\n\n\nChapter 11: Corpus Studies\n\n\n\n\n\n  Ch. 11 - Genre Classification\nChapter11.2.ipynb\n\nPython\n\n\n  Ch. 11 - Synchrony\nChapter11.3.qmd\n\nR\n\n\nChapter 12: Summary and Future Directions\n\n\n\n\n\nAppendix\n\n\n\n\n\n  Citation\n\n\nMarkdown\n\n\n  Technical\n\n\nMarkdown\n\n\n  Links\n\n\nMarkdown\n\n\n  Version (R)\nVersion_R.ipynb\n\nR\n\n\n  Version (Python)\nVersion_Python.ipynb\n\nPython\n\n\n\n\n\n\n\n Back to top"
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