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Data Skills for Media Professionals
A Basic Guide
Ken Blake (Author), Jason Reineke (Author)
9781119118961, Wiley
Paperback / softback, published 1 October 2019
224 pages
22.9 x 15.2 x 1.3 cm, 0.295 kg
Teaches the basic, yet all-important, data skills required by today’s media professionals The authors of Data Skills for Media Professionals have assembled a book that teaches key aspects of data analysis, interactive data visualization and online map-making through an introduction to Google Drive, Google Sheets, and Google My Maps, all free, highly intuitive, platform-agnostic tools available to any reader with a computer and a web connection. Delegating the math and design work to these apps leaves readers free to do the kinds of thinking that media professionals do most often: considering what questions to ask, how to ask them, and how to evaluate and communicate the answers. Although focused on Google apps, the book draws upon complementary aspects of the free QGIS geographic information system, the free XLMiner Analysis ToolPak Add-on for Google Sheets, and the ubiquitous Microsoft Excel spreadsheet application. Worked examples rely on frequently updated data from the U.S. Bureau of Labor Statistics, the Federal Election Commission, the National Bridge Inventory of structurally deficient bridges, and other federal sources, giving readers the option of immediately applying what they learn to current data they can localize to any area in the United States. The book offers chapters covering: basic data analysis; data visualization; making online maps; Microsoft Excel and pivot tables; matching records with Excel's VLOOKUP function; basic descriptive and inferential statistics; and other functions, tools and techniques. Data Skills of Media Professionals is an excellent book for students taking skills courses in the more than 100 ACEJMC-accredited journalism and mass communication programs across the United States. It would also greatly benefit those enrolled in advanced or specialized reporting courses, including courses dedicated solely to teaching data skills.
Preface ix 1 Basic Data Analysis 1 Some Example Data 1 An Introductory Tool: Google Sheets 3 Getting the Data into a Google Sheet 4 Getting a Fixed Copy of the Data 9 Formatting the Data 11 Cleaning the Data 12 Planning your Analysis 13 Filtering 14 Calculating 17 Labeling and Tidying Up 21 Sorting 22 Where’s the “Save” Button? 24 Writing About the Analysis Results 24 Recap 26 References 26 2 Data Visualization 27 Preparing Your Data 28 Making a Column Chart 29 Publishing the Chart to the Web 33 Choosing the Right Type of Chart 35 Recap 41 References 41 3 Making Online Maps 43 Downloading a Shapefile 44 Importing the Shapefile into QGIS 45 Examining the Shapefile and Joining it with the Unemployment Data 47 Customizing and Publishing the Map File with Google My Maps 54 Mapping Specific Points with Latitude and Longitude Coordinates 64 Mapping Specific Points with Addresses 73 Making a Map When You Have no Geolocation Data to Import 77 Recap 83 References 84 4 Microsoft Excel and PivotTables 85 Introducing PivotTables 85 Getting Started: Aggregating Contributions by City 89 Using the PivotTable Tool’s “Filters” Box 92 Using the PivotTable Tool’s “Columns” Box 94 Investigating Relatedness 96 Spotting the Absence of a Relationship 105 Downloading Campaign Finance Data from the Federal Election Commission 107 Excel vs. Google Sheets 111 Recap 112 References 113 5 Matching Records with Excel’s VLOOKUP 115 Overview 118 Aggregating each Candidate’s Donations by Source 119 Using VLOOKUP 122 Using Filters to Create a Classification Column 127 VLOOKUP Pitfalls 129 Recap 131 References 131 6 Google Sheets and Inferential Statistics 133 Sampling and Assumptions of Inferential Statistics 134 Getting the Data and Installing the XLMiner Google Sheets Add‐on 136 Computing and Understanding Basic Inferential Statistics 138 Descriptive Statistics and Confidence Intervals 140 The One‐sample T‐test 143 The One‐sample Chi‐square Test 148 Knowing which Test to Use 152 Computing and Understanding Basic Bivariate Statistics 154 Two‐sample T‐tests 154 Chi‐square Analysis of a PivotTable 158 Correlation Between Two Continuous Variables: Regression 164 Recap 169 References 170 7 Other Functions, Tools and Techniques 171 DATE, NOW, and DATEDIF 171 AVERAGE, STDEV, MEDIAN, MIN, MAX 173 RAND 175 LEFT, MID, and RIGHT 175 The “Text to Columns” Wizard 177 CONCATENATE 179 IF and IFS 180 IFERROR 182 COMBIN and PERMUT 183 Google Forms 184 Comparing Numbers Over Time 187 Adjusting for Inflation 187 Adjusting for Population Changes 188 Recap 190 References 190 Index 191
Subject Areas: Sociology & anthropology [JH]
