MARC Record from marc_columbia

LEADER: 05746cam a2200733 i 4500
001 15922027
005 20220604235113.0
006 m o d
007 cr |||||||||||
008 210813t20222022nyu ob 001 0 eng
010 $a 2021040165
035 $a(OCoLC)on1264175212
035 $a(NNC)15922027
040 $aDLC$beng$erda$cDLC$dOCLCO$dOCLCF$dTYFRS$dYDX$dOCLCO$dUKMGB$dN$T$dYDX$dOCLCO
015 $aGBC1L3630$2bnb
016 7 $a020432838$2Uk
020 $a9781003200475$qelectronic book
020 $a1003200478$qelectronic book
020 $a9781000534764$qepub
020 $a1000534766$qepub
020 $a9781000534672$qelectronic book
020 $a1000534677$qelectronic book
020 $z9781032060521$qhardcover
020 $z9781032060491$qpaperback
024 7 $a10.4324/9781003200475$2doi
035 $a(OCoLC)1264175212
037 $a9781003200475$bTaylor & Francis
042 $apcc
050 4 $aMT1.W438$bF76 2022
072 7 $aMUS$x000000$2bisacsh
072 7 $aMUS$x022000$2bisacsh
072 7 $aSOC$x027000$2bisacsh
072 7 $aGPS$2bicssc
082 04 $a780.71$223
049 $aZCUA
100 1 $aWesolowski, Brian C.,$eauthor.
245 10 $aFrom data to decisions in music education research :$bdata analytics and the general linear model using R /$cBrian C. Wesolowski.
264 1 $aNew York, NY :$bRoutledge,$c2022.
264 4 $c©2022
300 $a1 online resource (xxvi, 493 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
504 $aIncludes bibliographical references and index.
505 0 $aSection I. Fundamentals and Principles of the R Programming Language. The R Programming Environment ; Data Types and Data Structures -- Section II. Data Wrangling Techniques. Data Preprocessing and Data Manipulation ; Data Aggregation -- Section III. Descriptive Analytics and Exploratory Data Analysis Techniques. Summary Operations ; Data Visualization -- Section IV. Diagnostic Analytics and Data Mining Techniques. Normality Assessment and Anomaly Detection ; Data Re-Expression Techniques ; Covariance and Correlation -- Section V. Predictive Analytics and the General Linear Model. The Mean Model and Simple Linear Regression ; Multiple Linear Regression ; Special Cases of the General Linear Model ; Model Diagnostics.
520 $a"From Data to Decisions in Music Education Research provides a structured and hands-on approach to working with empirical data in the context of music education research. Using step-by-step tutorials with in-depth examples of music education data and research questions, this text draws upon concepts in data science and statistics to provide a comprehensive framework for working with a variety of data and solving data-driven problems. All of the skills presented here use the R programming language, a free, open-source statistical computing and graphics environment. Using R enables readers to refine their computational thinking abilities and data literacy skills while facilitating reproducibility, replication, and transparency of data analysis in the field. The book offers: A clear and comprehensive framework for thinking about data analysis processes in a music education context. An overview of common data structures and data types used in statistical programming and data analytics. Techniques for cleaning, preprocessing, manipulating, aggregating, and mining data in ways that facilitate organization and interpretation. Methods for summarizing and visualizing data to help identify structures, patterns, and trends within data sets. Detailed applications of descriptive, diagnostic, and predictive analytics processes. Step-by-step code for all concepts and analyses. Direct access to all data sets and R script files through the accompanying eResource. From Data to Decisions in Music Education Research offers a reference "cookbook" of code and programming recipes written with the graduate music education student in mind and breaks down data analysis skills in an approachable fashion. It can be used across a wide range of graduate music education courses that rely on the application of empirical data analyses and will be useful to all music education scholars and professionals seeking to enhance their use of quantitative data"--$cProvided by publisher.
545 0 $aBrian C. Wesolowski is an Associate Professor of Music Education at the University of Georgia. He received his Ph.D. from the University of Miami, Coral Gables, FL.
588 $aDescription based on online resource; title from digital title page (viewed on May 02, 2022).
650 0 $aMusic$xInstruction and study$xResearch.
650 0 $aEducational planning$xStatistical methods.
650 0 $aR (Computer program language)
650 6 $aMusique$xÉtude et enseignement$xRecherche.
650 6 $aÉducation$xPlanification$xMéthodes statistiques.
650 6 $aR (Langage de programmation)
650 7 $aMUSIC / General$2bisacsh
650 7 $aMUSIC / Instruction & Study / General$2bisacsh
650 7 $aSOCIAL SCIENCE / Statistics$2bisacsh
650 7 $aEducational planning$xStatistical methods.$2fast$0(OCoLC)fst00903562
650 7 $aMusic$xInstruction and study$xResearch.$2fast$0(OCoLC)fst01030367
650 7 $aR (Computer program language)$2fast$0(OCoLC)fst01086207
655 4 $aElectronic books.
776 08 $iPrint version:$aWesolowski, Brian C.$tFrom data to decisions in music education research$dNew York : Routledge, 2022$z9781032060521$w(DLC) 2021040164
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15922027$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS