Description

Book Synopsis

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

Table of Contents

Chapter 1: Data Defined Climbing the pyramid A brief history of the data world Data file formats Chapter 2: Clues for uncovering data Why agencies collect, analyze, publish data Clues from data entry Clues from reports Tricks to uncover forms and reports On your own Chapter 3: Online databases Destination: data portals Statistical stockpiles Agency sites Non-governmental resources Data search tricks Don’t forget the road map On your own Chapter 4: Identifying and requesting offline data Other clues for offline data Find the data nerd Requesting the data Writing the data request FOIA in action Negotiating through obstacles Getting help On your own Chapter 5: Data dirt is everywhere All data are dirty Detecting dirt in agricultural data Changed rules = changed data On your own Chapter 6: Data integrity checks Big-picture checks Detailed checks On your own Chapter 7: Getting your data in shape Column carving Concatenate to paste Date tricks Power scrubbing with OpenRefine Extracting data from PDFs On your own Chapter 8: Number summaries and comparisons Simple summary statistics Compared to what? Benchmarking On your own Chapter 9: Calculating summary statistics and number comparisons Sum crimes by year Minimum and maximum numbers Amount change Stepping up to percent change Running rates Running ratios Percent of total More summarizing On your own Chapter 10: Spreadsheets as database managers Sorting Filtering records Grouping and summarizing On your own Chapter 11: Visualizing your data Data visualization defined Some best practices Chapter 12: Charting choices Visualizing data with charts On your own Chapter 13: Charting in Excel Pie chart Horizontal bar charts Column and line charts Scatterplot Stock chart Sparklines On your own Chapter 14: Charting with Web tools Online visualization options Evaluating web visualization platforms Creating Fusion Table charts On your own Chapter 15: Taking analysis to the next level Database managers Statistical programs

Data Literacy

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    A Paperback by David L. L. Herzog

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      Book details

      Publisher Sage Publications
      Published 7 April 2015
      ISBN-13 9781483333465
      978-1483333465
      ISBN-10 1483333469

      Description

      Book Synopsis

      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

      Table of Contents

      Chapter 1: Data Defined Climbing the pyramid A brief history of the data world Data file formats Chapter 2: Clues for uncovering data Why agencies collect, analyze, publish data Clues from data entry Clues from reports Tricks to uncover forms and reports On your own Chapter 3: Online databases Destination: data portals Statistical stockpiles Agency sites Non-governmental resources Data search tricks Don’t forget the road map On your own Chapter 4: Identifying and requesting offline data Other clues for offline data Find the data nerd Requesting the data Writing the data request FOIA in action Negotiating through obstacles Getting help On your own Chapter 5: Data dirt is everywhere All data are dirty Detecting dirt in agricultural data Changed rules = changed data On your own Chapter 6: Data integrity checks Big-picture checks Detailed checks On your own Chapter 7: Getting your data in shape Column carving Concatenate to paste Date tricks Power scrubbing with OpenRefine Extracting data from PDFs On your own Chapter 8: Number summaries and comparisons Simple summary statistics Compared to what? Benchmarking On your own Chapter 9: Calculating summary statistics and number comparisons Sum crimes by year Minimum and maximum numbers Amount change Stepping up to percent change Running rates Running ratios Percent of total More summarizing On your own Chapter 10: Spreadsheets as database managers Sorting Filtering records Grouping and summarizing On your own Chapter 11: Visualizing your data Data visualization defined Some best practices Chapter 12: Charting choices Visualizing data with charts On your own Chapter 13: Charting in Excel Pie chart Horizontal bar charts Column and line charts Scatterplot Stock chart Sparklines On your own Chapter 14: Charting with Web tools Online visualization options Evaluating web visualization platforms Creating Fusion Table charts On your own Chapter 15: Taking analysis to the next level Database managers Statistical programs

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