Statistics In Musicology Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Statistics In Musicology book. This book definitely worth reading, it is an incredibly well-written.
Traditionally, statistics and music are not generally associated with each other. However, ...intelligent... music software, computer digitization, and other advanced techniques and technologies have precipitated the need for standard statistical models to answer basic musicological questions. Statistics In Musicology presents an unprecedented introduction to statistical and mathematical methods developed for use in music analysis, music theory, and performance theory. It explores concrete methods for data generation and numerical encoding of musical data and serves as a practical reference for a wide audience, including statisticians, mathematicians, musicologists, and musicians.
Traditionally, statistics and music are not generally associated with each other. However, ...intelligent... music software, computer digitization, and other advanced techniques and technologies have precipitated the need for standard statistical models to answer basic musicological questions. Statistics In Musicology presents an unprecedented introduction to statistical and mathematical methods developed for use in music analysis, music theory, and performance theory. It explores concrete methods for data generation and numerical encoding of musical data and serves as a practical reference for a wide audience, including statisticians, mathematicians, musicologists, and musicians.
Statistics in Music Education Research by Joshua A. Russell Pdf
In Statistics in Music Education Research, author Joshua Russell explains the process of using a range of statistical analyses from inception to research design to data entry to final analysis using understandable descriptions and examples from extant music education research. He explores four main aspects of music education research: understanding logical concepts of statistical procedures and their outcomes; critiquing the use of different procedures in extant and developing research; applying the correct statistical model for not only any given dataset, but also the correct logic determining which model to employ; and reporting the results of a given statistical procedure clearly and in a way that provides adequate information for the reader to determine if the data analysis is accurate and interpretable. While it is written predominately for graduate students in music education courses, Statistics in Music Education Research will also help music education researchers and teachers of music educators gain a better understanding of how parametric statistics are employed and interpreted in music education.
Music Data Analysis by Claus Weihs,Dietmar Jannach,Igor Vatolkin,Guenter Rudolph Pdf
This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user interface and hardware. It is ideal for use in university classes with an interest in music data analysis. It also could be used in computer science and statistics as well as musicology.
Traditionally, statistics and music are not generally associated with each other. However, ...intelligent... music software, computer digitization, and other advanced techniques and technologies have precipitated the need for standard statistical models to answer basic musicological questions. Statistics In Musicology presents an unprecedented intr
Music by Numbers by Richard Osborne,Dave Laing Pdf
The music industries are fuelled by statistics: sales targets, breakeven points, success ratios, royalty splits, website hits, ticket revenues, listener figures, piracy abuses and big data. Statistics are of consequence. They influence the music that consumers get to hear, they determine the revenues of music makers, and they shape the policies of governments and legislators. Yet many of these statistics are generated by the music industries themselves, and their accuracy can be questioned. This original new book sets out to explore this shadowy terrain. While there are books that offer guidelines about how the music industries work, as well as critiques from academics about the policies of music companies, this is the first book that takes a sustained look at these subjects from a statistical angle. This is particularly significant as statistics have not just been used to explain the music industries, they are also essential to the ways that the industries work: they drive signing policy, contractual policy, copyright policy, economic policy and understandings of consumer behaviour. This edited collection provides the first in-depth examination of the use and abuse of statistics in the music industries. The international group of contributors are noted music business scholars and practitioners in the field. The book addresses five key areas in which numbers are employed: sales and awards; royalties and distribution; music piracy; music policy; and audiences and their uses of music. The authors address these subjects from a range of perspectives. Some of them test the veracity of this data and explore its tactical use by music businesses. Others are helping to generate these numbers: they are developing surveys and online projects and offer candid self-observations in this volume. There are also authors who have been subject to statistics; they deliver first-hand accounts of music industry reporting. The digital age is inherently numerical. Within the music industries this has prompted new ways of tracking the usage and recompense of music. In addition, it has generated new means of monitoring and engaging audience behaviour. It has also led to increased documentation of the trade. There is more reporting of the overall revenues of music industry sectors. There is also more engagement between industry and academia when it comes to conducting analyses and offering numerical recommendations to politicians. The aim of this collection is to expose the culture and politics of data. Music industry statistics are all-pervasive, yet because of this ubiquity they have been under-explored. This book provides new ways by which to learn music by numbers. A timely examination of how data and statistics are key to the music industries. Widely held industry assumptions are challenged with data from a variety of sources and in an engaging, lucid manner. Highly recommended for anyone with an interest in how the music business uses and manipulates the data that digital technologies have made available. Primary readership will be among popular music academics, undergraduate and postgraduate students working in the fields of popular music studies, music business, media studies, cultural studies, sociology and creative industries. The book will also be of interest to people working within the music industries and to those whose work encounters industry statistics.
Music Data Mining by Tao Li,Mitsunori Ogihara,George Tzanetakis Pdf
The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to
Music Research Data Management by Amy S. Jackson,Sean Luyk Pdf
What is research data for music researchers and performers? How can music librarians develop their knowledge and skills to better meet the research data needs of their constituents, and contribute to the data-intensive turn in academia? Music Research Data Management: A Guide for Librarians explores these questions, provides readers with a background in research data management as it applies to specific music disciplines, and presents examples of the data used within several of the major music and music-related disciplines. Many academic libraries offer extensive research data management services, which may include support for data management planning, data description and access, preservation, and the promotion of open data initiatives. Because of a lack of shared vocabulary, music researchers may not realize that they work with “data” and are eligible for these services. Music researchers and performers work with items such as texts, datasets, and recordings, and create new items for the library to curate and preserve. By drawing upon research data management principles, music librarians can define music research data and articulate its importance. Music Research Data situates research data management within the music disciplines and examines how music librarians can become leaders in the evolving turn towards data-focused research and scholarship, including ways in which our libraries can better support and curate these data. Useful to music librarians with varying levels of experience and development in research data management services at their libraries, this book offers a solid foundation for building these services.
Author : Brian C. Wesolowski Publisher : Taylor & Francis Page : 520 pages File Size : 46,5 Mb Release : 2022-02-22 Category : Music ISBN : 9781000534672
From Data to Decisions in Music Education Research by Brian C. Wesolowski Pdf
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, this book 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. From Data to Decisions in Music Education Research offers a reference "cookbook" of code and programming recipes written with the graduate music education student in mind and breaks down data analysis processes and skills in an approachable fashion. It can be used across a wide range of graduate music education courses that rely on the application of empirical data analyses and will be useful to all music education scholars and professionals seeking to enhance their use of quantitative data.
This book shows how information theory, probability, statistics, mathematics and personal computers can be applied to the exploration of numbers and proportions in music. It brings the methods of scientific and quantitative thinking to questions like: What are the ways of encoding a message in music and how can we be sure of the correct decoding? How do claims of names hidden in the notes of a score stand up to scientific analysis? How many ways are there of obtaining proportions and are they due to chance? After thoroughly exploring the ways of encoding information in music, the ambiguities of numerical alphabets and the words to be found “hidden” in a score, the book presents a novel way of exploring the proportions in a composition with a purpose-built computer program and gives example results from the application of the techniques. These include information theory, combinatorics, probability, hypothesis testing, Monte Carlo simulation and Bayesian networks, presented in an easily understandable form including their development from ancient history through the life and times of J. S. Bach, making connections between science, philosophy, art, architecture, particle physics, calculating machines and artificial intelligence. For the practitioner the book points out the pitfalls of various psychological fallacies and biases and includes succinct points of guidance for anyone involved in this type of research. This book will be useful to anyone who intends to use a scientific approach to the humanities, particularly music, and will appeal to anyone who is interested in the intersection between the arts and science. With a foreword by Ruth Tatlow (Uppsala University), award winning author of Bach’s Numbers: Compositional Proportion and Significance and Bach and the Riddle of the Number Alphabet. “With this study Alan Shepherd opens a much-needed examination of the wide range of mathematical claims that have been made about J. S. Bach's music, offering both tools and methodological cautions with the potential to help clarify old problems.” Daniel R. Melamed, Professor of Music in Musicology, Indiana University
Computational Musicology in Hindustani Music by Soubhik Chakraborty,Guerino Mazzola,Swarima Tewari,Moujhuri Patra Pdf
The book opens with a short introduction to Indian music, in particular classical Hindustani music, followed by a chapter on the role of statistics in computational musicology. The authors then show how to analyze musical structure using Rubato, the music software package for statistical analysis, in particular addressing modeling, melodic similarity and lengths, and entropy analysis; they then show how to analyze musical performance. Finally, they explain how the concept of seminatural composition can help a music composer to obtain the opening line of a raga-based song using Monte Carlo simulation. The book will be of interest to musicians and musicologists, particularly those engaged with Indian music.
Applications in Statistical Computing by Nadja Bauer,Katja Ickstadt,Karsten Lübke,Gero Szepannek,Heike Trautmann,Maurizio Vichi Pdf
This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.
Presents national statistics on various aspects of music education, including degrees awarded, teacher certification status, teacher employment rates and opportunities.
Statistics in Music Education Research by Joshua A. Russell Pdf
In Statistics in Music Education Research, author Joshua Russell explains the process of using a range of statistical analyses from inception to research design to data entry to final analysis using understandable descriptions and examples from extant music education research. He explores four main aspects of music education research: understanding logical concepts of statistical procedures and their outcomes; critiquing the use of different procedures in extant and developing research; applying the correct statistical model for not only any given dataset, but also the correct logic determining which model to employ; and reporting the results of a given statistical procedure clearly and in a way that provides adequate information for the reader to determine if the data analysis is accurate and interpretable. While it is written predominately for graduate students in music education courses, Statistics in Music Education Research will also help music education researchers and teachers of music educators gain a better understanding of how parametric statistics are employed and interpreted in music education.
