How to avoid 10 common mistakes in data reporting by Catherine Sheffo.
From the post:
After getting your hands on a data set, the hardest part of incorporating data analysis into your beat is getting started — and avoiding beginners’ pitfalls along the way.
From scrambled columns to unintelligible field names, every file you receive with comes with challenges for new and experienced data reporters alike.
We talked to Sean Mussenden, chief of the data and graphics bureau at the University of Maryland’s Capital News Service, about 10 mistakes to avoid while you establish a workflow and get comfortable with data sets in your day-to-day reporting.
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Topic map fans will recognize #5:
Mistake No. 5 – Assuming you know what the field names mean
That can easily extend to what is in the fields as well.
I would add:
Mistake No. 11 – Assuming data is truthful and unbiased
Always bear in mind data given to you has been “cooked.”
Data has been omitted, changed or added, however “raw” the data may appear to you. The act of collecting data involves omission, changes and additions. All from a point of view.
Not to mention whoever gave you data had an agenda as well.
There’s no escape from bias but you can work at serving your own agenda and not those of others.