Data Literacy

A User's Guide

Häftad, Engelska, 2015

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A practical, skill-based introduction to data analysis and literacy

We are swimming in a world of data, and this handy guide will keep you afloat while you learn to make sense of it all. In Data Literacy: A User's Guide, David Herzog, a journalist with a decade of experience using data analysis to transform information into captivating storytelling, introduces students and professionals to the fundamentals of data literacy, a key skill in today’s world. Assuming the reader has no advanced knowledge of data analysis or statistics, this book shows how to create insight from publicly-available data through exercises using simple Excel functions. Extensively illustrated, step-by-step instructions within a concise, yet comprehensive, reference will help readers identify, obtain, evaluate, clean, analyze and visualize data. A concluding chapter introduces more sophisticated data analysis methods and tools including database managers such as Microsoft Access and MySQL and standalone statistical programs such as SPSS, SAS and R.

Produktinformation

Utgivningsdatum2015-04-07
Mått152 x 228 x 17 mm
Vikt340 g
FormatHäftad
SpråkEngelska
Antal sidor224
Upplaga1
FörlagSAGE Publications
ISBN9781483333465

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David Herzog is an associate professor at the Missouri School of Journalism, where he also serves as the academic adviser to the National Institute for Computer-Assisted Reporting. He was a fellow at the Reynolds Journalism Institute, where he launched OpenMissouri.org, a directory of data held offline by state agencies. Before arriving at the School of Journalism in 2002, he worked as a newspaper reporter at The Providence Journal, The Baltimore Sun and The Morning Call in Allentown, PA. He is a native of Bethlehem, PA.

Chapter 1: Data DefinedClimbing the pyramidA brief history of the data worldData file formatsChapter 2: Clues for uncovering dataWhy agencies collect, analyze, publish dataClues from data entryClues from reportsTricks to uncover forms and reportsOn your ownChapter 3: Online databasesDestination: data portalsStatistical stockpilesAgency sitesNon-governmental resourcesData search tricksDon’t forget the road mapOn your ownChapter 4: Identifying and requesting offline dataOther clues for offline dataFind the data nerdRequesting the dataWriting the data requestFOIA in actionNegotiating through obstaclesGetting helpOn your ownChapter 5: Data dirt is everywhereAll data are dirtyDetecting dirt in agricultural dataChanged rules = changed dataOn your ownChapter 6: Data integrity checksBig-picture checksDetailed checksOn your ownChapter 7: Getting your data in shapeColumn carvingConcatenate to pasteDate tricksPower scrubbing with OpenRefineExtracting data from PDFsOn your ownChapter 8: Number summaries and comparisonsSimple summary statisticsCompared to what?BenchmarkingOn your ownChapter 9: Calculating summary statistics and number comparisonsSum crimes by yearMinimum and maximum numbersAmount changeStepping up to percent changeRunning ratesRunning ratiosPercent of totalMore summarizingOn your ownChapter 10: Spreadsheets as database managersSortingFiltering recordsGrouping and summarizingOn your ownChapter 11: Visualizing your dataData visualization definedSome best practicesChapter 12: Charting choicesVisualizing data with chartsOn your ownChapter 13: Charting in ExcelPie chartHorizontal bar chartsColumn and line chartsScatterplotStock chartSparklinesOn your ownChapter 14: Charting with Web toolsOnline visualization optionsEvaluating web visualization platformsCreating Fusion Table chartsOn your ownChapter 15: Taking analysis to the next levelDatabase managersStatistical programs