Data Journalism 101 - Part 2 by Michael J. Berens
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The document outlines a data journalism session focused on utilizing data for effective storytelling, particularly in the context of hunting-related injuries. It discusses methods for sorting and filtering data, as well as the importance of calculations to substantiate claims about issues like salary discrepancies in sports coaching versus teaching. The session aims to guide journalists in interviewing data to provide conclusive insights rather than relying on anecdotal evidence.
Data Journalism 101 - Part 2 by Michael J. Berens
- 1. Data Journalism 101 Session Two: Working with Data Sort * Filter * Calculations Excellence in Journalism Conference 2014 Donald W. Reynolds National Center for Business Journalism at ASU Michael J. Berens – !e Seattle Times
- 2. !e Tip — It’s hunting season, again, and your editor wants a daily story about this seasonal rite of passage. — What is the most common type of injury? — What day was the deadliest for hunters? — How often is impairment (drugs / alcohol) a factor? — And dozens of other questions — “Interview the data”
- 4. Sorting
- 5. Filter
- 6. Pivot tables
- 7. !e Tip • Sources say that football coaches routinely earn higher salaries than the most experienced teachers. • Anecdotally, it appears to be true but other sources say it’s an isolated issue. • How do you attack the story and QUANTIFY the issue conclusively – avoiding the he said, she said conundrum?
- 8. Calculations