If you’re in North America, please visit our Sage College Publishing website to purchase or sample this book:
Go to College Publishing WebsiteDescription
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.
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.
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
Additional materials
Description
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.
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.
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
Additional materials
Reviews
February 2015 | 224 pages | Sage US
| Format | Published Date | ISBN | Price |
|---|
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.
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.
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
Recent Product Reviews:
Great overview of the data process using spreadsheets, which seems reachable for our students.
Ms Miren Berasategi, Communications, University of Deusto in San Sebastian
It is a very useful and easy-to-follow book. I intend to recommend it to my students as a complimentary source to gain an understanding of the context, concepts and main steps for doing data driven journalism.
Mrs Özlem Erkmen, Communication Sciences, Dogus University