From Data to Decisions in Music Education Research
From Data to Decisions in Music Education Research provides a structured and hands-on approach to working with empirical data in the context of music education research. Using step-by-step tutorials with in-depth examples of music education data and research questions, this text draws upon concepts in data science and statistics to provide a comprehensive framework for working with a variety of data and solving data-driven problems.
All of the skills presented here use the R programming language, a free, open-source statistical computing and graphics environment. Using R enables readers to refine their computational thinking abilities and data literacy skills while facilitating reproducibility, replication, and transparency of data analysis in the field. The book offers:
- A clear and comprehensive framework for thinking about data analysis processes in a music education context.
- An overview of common data structures and data types used in statistical programming and data analytics.
- Techniques for cleaning, preprocessing, manipulating, aggregating, and mining data in ways that facilitate organization and interpretation.
- Methods for summarizing and visualizing data to help identify structures, patterns, and trends within data sets.
- Detailed applications of descriptive, diagnostic, and predictive analytics processes.
- Step-by-step code for all concepts and analyses.
- Direct access to all data sets and R script files through the accompanying eResource.